FL7: Add MIRROR_PAD CPU reference implementation and functional testing
Also refined MIRROR_PAD specification.
Also updated sample shim driver prebuilts.
Test: NeuralNetworksTest_static --gtest_filter=*reverse_dim*:*abs*:*floor*:*log*:*rsqrt*:*sin*:*sqrt*:*mirror_pad*
Test: atest CtsNNAPITestCases -- --test-arg com.android.tradefed.testtype.GTest:native-test-flag:"--gtest_filter=*reverse_dim*:*abs*:*floor*:*log*:*rsqrt*:*sin*:*sqrt*:*mirror_pad*"
Test: atest VtsHalNeuralnetworksTargetTest -- --test-arg com.android.tradefed.testtype.GTest:native-test-flag:"--gtest_filter=*reverse_dim*:*abs*:*floor*:*log*:*rsqrt*:*sin*:*sqrt*:*mirror_pad*"
Bug: 202280925
Merged-In: Ib2b310365e76364bb7c2fa56cb73b0a788e23123
Change-Id: Ib2b310365e76364bb7c2fa56cb73b0a788e23123
(cherry picked from commit a0e7d007bf92468e890e8baf78a417fcc6ad48c4)
diff --git a/common/include/nnapi/OperationTypes.h b/common/include/nnapi/OperationTypes.h
index 71903d0..e8a8524 100644
--- a/common/include/nnapi/OperationTypes.h
+++ b/common/include/nnapi/OperationTypes.h
@@ -5316,6 +5316,18 @@
/**
* Pads a tensor with mirrored values.
*
+ * This operator specifies one of two padding modes: REFLECT or SYMMETRIC.
+ * In the case of REFLECT mode, the mirroring excludes the border element
+ * on the padding side.
+ * In the case of SYMMETRIC mode, the mirroring includes the border element
+ * on the padding side.
+ *
+ * For example, if the input is the 1-D tensor `[1, 2, 3]` and the padding
+ * is `[0, 2]` (i.e., pad no elements before the first (and only) dimension,
+ * and two elements after the first (and only) dimension), then:
+ * - REFLECT mode produces the output `[1, 2, 3, 2, 1]`
+ * - SYMMETRIC mode produces the output `[1, 2, 3, 3, 2]`
+ *
* Supported tensor {@link OperandType}:
* * {@link OperandType::TENSOR_FLOAT16}
* * {@link OperandType::TENSOR_FLOAT32}
@@ -5334,6 +5346,11 @@
* front of dimension i.
* padding[i, 1] specifies the number of elements to be padded after the
* end of dimension i.
+ * Each padding value must be nonnegative.
+ * In the case of REFLECT mode, each padding value must be less than the
+ * corresponding dimension.
+ * In the case of SYMMETRIC mode, each padding value must be less than or
+ * equal to the corresponding dimension.
* * 2: An {@link OperandType::INT32} scalar, specifying the mode.
* Options are 0:REFLECT and 1:SYMMETRIC.
*
diff --git a/common/operations/MirrorPad.cpp b/common/operations/MirrorPad.cpp
index 3eff61c..37572dd 100644
--- a/common/operations/MirrorPad.cpp
+++ b/common/operations/MirrorPad.cpp
@@ -20,14 +20,8 @@
#include "OperationsUtils.h"
#ifdef NN_INCLUDE_CPU_IMPLEMENTATION
-
-#if 0
-#pragma clang diagnostic push
-#pragma clang diagnostic ignored "-Wunused-parameter"
-#pragma clang diagnostic ignored "-Wsign-compare"
-#include <tensorflow/lite/kernels/internal/reference/reference_ops.h>
-#pragma clang diagnostic pop
-#endif
+#include <limits>
+#include <vector>
#include "CpuOperationUtils.h"
#endif // NN_INCLUDE_CPU_IMPLEMENTATION
@@ -48,6 +42,9 @@
constexpr uint32_t kNumOutputs = 1;
constexpr uint32_t kOutputTensor = 0;
+[[maybe_unused]] constexpr int kModeReflect = 0;
+[[maybe_unused]] constexpr int kModeSymmetric = 1;
+
Result<Version> validate(const IOperationValidationContext* context) {
NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs);
NN_RET_CHECK_EQ(context->getNumOutputs(), kNumOutputs);
@@ -113,19 +110,215 @@
}
#ifdef NN_INCLUDE_CPU_IMPLEMENTATION
-bool prepare(IOperationExecutionContext* /*context*/) {
- return false;
+bool prepare(IOperationExecutionContext* context) {
+ // Input tensor must be of positive rank.
+ const Shape inputShape = context->getInputShape(kInputTensor);
+ const auto inputRank = getNumberOfDimensions(inputShape);
+ NN_RET_CHECK_GT(inputRank, 0U);
+
+ // Check mode value.
+ const int32_t mode = context->getInputValue<int32_t>(kInputModeScalar);
+ NN_RET_CHECK(mode == kModeReflect || mode == kModeSymmetric);
+
+ Shape outputShape = context->getOutputShape(kOutputTensor);
+ NN_RET_CHECK(padPrepare(inputShape, context->getInputBuffer<int32_t>(kInputPaddingTensor),
+ context->getInputShape(kInputPaddingTensor), &outputShape));
+
+ // Check padding values.
+ // Note that the call to padPrepare() above verifies that the padding tensor
+ // has the correct dimensions.
+ {
+ const int32_t* paddingValues = context->getInputBuffer<int32_t>(kInputPaddingTensor);
+ for (uint32_t i = 0; i < inputRank; ++i) {
+ const int32_t paddingMax = getSizeOfDimension(inputShape, i) - (mode == kModeReflect);
+ const int32_t beforePadding = *(paddingValues++);
+ NN_RET_CHECK_GE(beforePadding, 0);
+ NN_RET_CHECK_LE(beforePadding, paddingMax);
+ const int32_t afterPadding = *(paddingValues++);
+ NN_RET_CHECK_GE(afterPadding, 0);
+ NN_RET_CHECK_LE(afterPadding, paddingMax);
+ }
+ }
+
+ return context->setOutputShape(kOutputTensor, outputShape);
}
-bool execute(IOperationExecutionContext* /*context*/) {
+/*-- begin execution ------------------------------------------------------------------*/
+
+// Based on
+// http://cs/android/external/tensorflow/tensorflow/lite/kernels/mirror_pad.cc;l=163;rcl=84f01780a69b5900cfddf2b44d696f92e0aac331
+
+// The structure of that code is largely preserved, for simplicity of comparison.
+
+// The TFLite implementation is multithreaded. The NNAPI implementation is not.
+
+namespace {
+
+// In adapting the TFLite implementation to NNAPI, we introduce conversions from
+// conventional NNAPI types (typically uint32_t) to int, which is the
+// conventional TFLite type. This function checks that such a conversion is
+// value-preserving.
+template <typename T>
+bool checkAsInt(T) {
+ // Making the assertion expression dependent on the template type (via
+ // incorportation of "&& sizeof(T)") ensures that the static_assert will
+ // only be evaluated if this function body is instantiated (we expect only
+ // the explicit specializations to be used). Alternatively, we could omit
+ // the body entirely, in which case an unexpected choice of T would result
+ // in a link-time failure rather than a compile-time failure.
+ static_assert(false && sizeof(T), "Unimplemented");
return false;
}
+template <>
+bool checkAsInt(uint32_t val) {
+ static_assert(sizeof(int) <= sizeof(uint32_t));
+ NN_RET_CHECK_LE(val, uint32_t(std::numeric_limits<int>::max()))
+ << kOperationName << " cannot represent value as int";
+ return true;
+}
+
+// Wrapper for data computed by the eval function.
+template <typename T>
+struct EvalData {
+ EvalData(const int* thePaddingTensor, Shape theInputTensorShape,
+ std::vector<int> theOutputDimsNumElements, std::vector<int> theInputDimsNumElements,
+ const T* theInputData, int theOffset, T* theOutputData, int theNumDims)
+ : paddingTensor(thePaddingTensor),
+ inputTensorShape(std::move(theInputTensorShape)),
+ outputDimsNumElements(std::move(theOutputDimsNumElements)),
+ inputDimsNumElements(std::move(theInputDimsNumElements)),
+ inputData(theInputData),
+ offset(theOffset),
+ outputData(theOutputData),
+ numDims(theNumDims) {}
+ const int32_t* paddingTensor = nullptr;
+ Shape inputTensorShape;
+ // Holds number of elements at the nth dimension.
+ // value at last dimension = 1, at second to last = sizeof last dimension.
+ std::vector<int> outputDimsNumElements;
+ std::vector<int> inputDimsNumElements;
+ const T* inputData = nullptr;
+
+ int offset = -1;
+ T* outputData = nullptr;
+ int numDims = 0;
+};
+
+// Helper function that obtains the left and right padding amounts.
+void getPadding(const int32_t* paddingTensor, int dimension, int32_t* leftPad, int32_t* rightPad) {
+ *leftPad = *(paddingTensor + dimension * 2);
+ *rightPad = *(paddingTensor + dimension * 2 + 1);
+}
+
+// Given dimension index and the left/right padding amounts.
+// Returns the corresponding dimension in the input array.
+int getInputDimension(int paddedDimension, const int leftPad, const int /* rightPad */,
+ const int inputDimSize, const int offset) {
+ if (paddedDimension < leftPad) {
+ const int originalInd = leftPad + offset - 1;
+ return originalInd - (std::min(paddedDimension, originalInd - offset));
+ }
+ paddedDimension -= leftPad;
+ if (paddedDimension >= inputDimSize) {
+ paddedDimension -= inputDimSize;
+ const int originalInd = inputDimSize - (1 + offset);
+ return originalInd - std::min(paddedDimension, originalInd);
+ }
+ return paddedDimension;
+}
+
+// Given an index in output array, returns the index of the value in input
+// array.
+template <typename T>
+int getFlatIndex(int index, const EvalData<T>& evalData) {
+ int flatIndex = 0;
+ for (int i = 0, nD = evalData.numDims; i < nD; ++i) {
+ int32_t leftPad, rightPad;
+ getPadding(evalData.paddingTensor, i, &leftPad, &rightPad);
+ const int dimensionIndex = index / evalData.outputDimsNumElements[i];
+ // getSizeOfDimension() undergoes checkAsInt() in eval().
+ const int indexInInput = getInputDimension(
+ dimensionIndex, leftPad, rightPad,
+ int(getSizeOfDimension(evalData.inputTensorShape, i)), evalData.offset);
+ flatIndex += indexInInput * evalData.inputDimsNumElements[i];
+ index %= evalData.outputDimsNumElements[i];
+ }
+ return flatIndex;
+}
+
+template <typename T>
+void run(const EvalData<T>& evalData, const int outputSize) {
+ // See MirrorPadWorkerTask::Run().
+ const auto* inputData = evalData.inputData;
+ auto* outputData = evalData.outputData;
+ for (int i = 0; i < outputSize; ++i) {
+ outputData[i] = inputData[getFlatIndex(i, evalData)];
+ }
+}
+} // namespace
+
+bool eval(IOperationExecutionContext* context) {
+ const Shape inputShape = context->getInputShape(kInputTensor);
+ const int32_t* padding = context->getInputBuffer<int32_t>(kInputPaddingTensor);
+ const int32_t mode = context->getInputValue<int32_t>(kInputModeScalar);
+ const Shape outputShape = context->getOutputShape(kOutputTensor);
+ const auto tensorType = context->getInputType(kInputTensor);
+
+ const uint32_t inputDims = getNumberOfDimensions(inputShape);
+ NN_RET_CHECK(checkAsInt(inputDims));
+ const int numDims = int(inputDims);
+
+ // checkAsInt() the individual dimensions here so we do not need to do so
+ // elsewhere.
+ for (int i = 0; i < numDims; ++i) {
+ const auto inputDim = getSizeOfDimension(inputShape, i);
+ NN_RET_CHECK(checkAsInt(inputDim));
+ const auto outputDim = getSizeOfDimension(outputShape, i);
+ NN_RET_CHECK(checkAsInt(outputDim));
+ }
+
+ std::vector<int> outputDimsNumElements(inputDims, 1);
+ std::vector<int> inputDimsNumElements(inputDims, 1);
+ for (int i = numDims - 2; i >= 0; i--) {
+ outputDimsNumElements[i] =
+ outputDimsNumElements[i + 1] * int(getSizeOfDimension(outputShape, i + 1));
+ inputDimsNumElements[i] =
+ inputDimsNumElements[i + 1] * int(getSizeOfDimension(inputShape, i + 1));
+ }
+
+ const int32_t offset = mode != kModeReflect ? 0 : 1;
+
+ const auto outputSize = getNumberOfElements(outputShape);
+
+#define MIRROR_PAD_CASE(operandType, dataType) \
+ case OperandType::operandType: { \
+ const EvalData evalData(padding, inputShape, std::move(outputDimsNumElements), \
+ std::move(inputDimsNumElements), \
+ context->getInputBuffer<dataType>(kInputTensor), offset, \
+ context->getOutputBuffer<dataType>(kOutputTensor), numDims); \
+ NN_RET_CHECK(checkAsInt(outputSize)); \
+ run(evalData, int(outputSize)); \
+ return true; \
+ }
+ switch (tensorType) {
+ MIRROR_PAD_CASE(TENSOR_FLOAT16, _Float16)
+ MIRROR_PAD_CASE(TENSOR_FLOAT32, float)
+ MIRROR_PAD_CASE(TENSOR_QUANT8_ASYMM, uint8_t)
+ MIRROR_PAD_CASE(TENSOR_QUANT8_ASYMM_SIGNED, int8_t)
+ MIRROR_PAD_CASE(TENSOR_INT32, int32_t)
+ default:
+ NN_RET_CHECK_FAIL() << "Unsupported tensor type for operation " << kOperationName;
+ }
+}
+
+/*-- end execution --------------------------------------------------------------------*/
+
#endif // NN_INCLUDE_CPU_IMPLEMENTATION
} // namespace mirror_pad_op
NN_REGISTER_OPERATION(MIRROR_PAD, mirror_pad_op::kOperationName, mirror_pad_op::validate,
- mirror_pad_op::prepare, mirror_pad_op::execute);
+ mirror_pad_op::prepare, mirror_pad_op::eval);
} // namespace nn
} // namespace android
diff --git a/driver/sample_shim/android_arm/neuralnetworks_sample_sl_driver_prebuilt.so b/driver/sample_shim/android_arm/neuralnetworks_sample_sl_driver_prebuilt.so
index 6571010..27c48a7 100755
--- a/driver/sample_shim/android_arm/neuralnetworks_sample_sl_driver_prebuilt.so
+++ b/driver/sample_shim/android_arm/neuralnetworks_sample_sl_driver_prebuilt.so
Binary files differ
diff --git a/driver/sample_shim/android_arm64/neuralnetworks_sample_sl_driver_prebuilt.so b/driver/sample_shim/android_arm64/neuralnetworks_sample_sl_driver_prebuilt.so
index 4e2b503..4183ec4 100755
--- a/driver/sample_shim/android_arm64/neuralnetworks_sample_sl_driver_prebuilt.so
+++ b/driver/sample_shim/android_arm64/neuralnetworks_sample_sl_driver_prebuilt.so
Binary files differ
diff --git a/driver/sample_shim/android_x86/neuralnetworks_sample_sl_driver_prebuilt.so b/driver/sample_shim/android_x86/neuralnetworks_sample_sl_driver_prebuilt.so
index 2779951..e0b5cf9 100755
--- a/driver/sample_shim/android_x86/neuralnetworks_sample_sl_driver_prebuilt.so
+++ b/driver/sample_shim/android_x86/neuralnetworks_sample_sl_driver_prebuilt.so
Binary files differ
diff --git a/driver/sample_shim/android_x86_64/neuralnetworks_sample_sl_driver_prebuilt.so b/driver/sample_shim/android_x86_64/neuralnetworks_sample_sl_driver_prebuilt.so
index 1f05e67..b299b93 100755
--- a/driver/sample_shim/android_x86_64/neuralnetworks_sample_sl_driver_prebuilt.so
+++ b/driver/sample_shim/android_x86_64/neuralnetworks_sample_sl_driver_prebuilt.so
Binary files differ
diff --git a/runtime/include/NeuralNetworksTypes.h b/runtime/include/NeuralNetworksTypes.h
index 2883f17..d953ed6 100644
--- a/runtime/include/NeuralNetworksTypes.h
+++ b/runtime/include/NeuralNetworksTypes.h
@@ -5759,6 +5759,18 @@
/**
* Pads a tensor with mirrored values.
*
+ * This operator specifies one of two padding modes: REFLECT or SYMMETRIC.
+ * In the case of REFLECT mode, the mirroring excludes the border element
+ * on the padding side.
+ * In the case of SYMMETRIC mode, the mirroring includes the border element
+ * on the padding side.
+ *
+ * For example, if the input is the 1-D tensor `[1, 2, 3]` and the padding
+ * is `[0, 2]` (i.e., pad no elements before the first (and only) dimension,
+ * and two elements after the first (and only) dimension), then:
+ * - REFLECT mode produces the output `[1, 2, 3, 2, 1]`
+ * - SYMMETRIC mode produces the output `[1, 2, 3, 3, 2]`
+ *
* Supported tensor {@link OperandCode}:
* * {@link ANEURALNETWORKS_TENSOR_FLOAT16}
* * {@link ANEURALNETWORKS_TENSOR_FLOAT32}
@@ -5777,6 +5789,11 @@
* front of dimension i.
* padding[i, 1] specifies the number of elements to be padded after the
* end of dimension i.
+ * Each padding value must be nonnegative.
+ * In the case of REFLECT mode, each padding value must be less than the
+ * corresponding dimension.
+ * In the case of SYMMETRIC mode, each padding value must be less than or
+ * equal to the corresponding dimension.
* * 2: An {@link ANEURALNETWORKS_INT32} scalar, specifying the mode.
* Options are 0:REFLECT and 1:SYMMETRIC.
*
diff --git a/runtime/test/generated/spec_AIDL_V3/mirror_pad.example.cpp b/runtime/test/generated/spec_AIDL_V3/mirror_pad.example.cpp
new file mode 100644
index 0000000..6756ca9
--- /dev/null
+++ b/runtime/test/generated/spec_AIDL_V3/mirror_pad.example.cpp
@@ -0,0 +1,5780 @@
+// Generated from mirror_pad.mod.py
+// DO NOT EDIT
+// clang-format off
+#include "TestHarness.h"
+using namespace test_helper;
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({22.738632088209073f, 25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 22.738632088209073f, 25.332655545751443f, 15.338241641058255f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f, 15.338241641058255f, 7.7675025087889f, 22.738632088209073f, 25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 22.738632088209073f, 25.332655545751443f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect = TestModelManager::get().add("mirror_pad_one_reflect", get_test_model_one_reflect());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({22.738632088209073f, 25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 22.738632088209073f, 25.332655545751443f, 15.338241641058255f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f, 15.338241641058255f, 7.7675025087889f, 22.738632088209073f, 25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 22.738632088209073f, 25.332655545751443f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // in_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // placeholder
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // param5
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_reflect_all_inputs_as_internal", get_test_model_one_reflect_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({22.738632088209073f, 25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 22.738632088209073f, 25.332655545751443f, 15.338241641058255f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f, 15.338241641058255f, 7.7675025087889f, 22.738632088209073f, 25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 22.738632088209073f, 25.332655545751443f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_one_reflect_all_tensors_as_inputs", get_test_model_one_reflect_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({22.738632088209073f, 25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 22.738632088209073f, 25.332655545751443f, 15.338241641058255f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f, 15.338241641058255f, 7.7675025087889f, 22.738632088209073f, 25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 22.738632088209073f, 25.332655545751443f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // in_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // placeholder1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // param6
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_reflect_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_one_reflect_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_float16() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({22.738632202148438f, 25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 22.738632202148438f, 25.33265495300293f, 15.338241577148438f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f, 15.338241577148438f, 7.767502307891846f, 22.738632202148438f, 25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 22.738632202148438f, 25.33265495300293f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_float16 = TestModelManager::get().add("mirror_pad_one_reflect_float16", get_test_model_one_reflect_float16());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_float16_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({22.738632202148438f, 25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 22.738632202148438f, 25.33265495300293f, 15.338241577148438f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f, 15.338241577148438f, 7.767502307891846f, 22.738632202148438f, 25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 22.738632202148438f, 25.33265495300293f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // in_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // placeholder2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // param7
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_float16_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_reflect_float16_all_inputs_as_internal", get_test_model_one_reflect_float16_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_float16_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({22.738632202148438f, 25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 22.738632202148438f, 25.33265495300293f, 15.338241577148438f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f, 15.338241577148438f, 7.767502307891846f, 22.738632202148438f, 25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 22.738632202148438f, 25.33265495300293f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_float16_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_one_reflect_float16_all_tensors_as_inputs", get_test_model_one_reflect_float16_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_float16_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({22.738632202148438f, 25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 22.738632202148438f, 25.33265495300293f, 15.338241577148438f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f, 15.338241577148438f, 7.767502307891846f, 22.738632202148438f, 25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 22.738632202148438f, 25.33265495300293f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // in_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // placeholder3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // param8
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_float16_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_reflect_float16_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_one_reflect_float16_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_quant8_asymm() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({207, 186, 105, 66, 127, 101}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({186, 207, 186, 105, 186, 207, 127, 66, 127, 101, 127, 66, 186, 207, 186, 105, 186, 207}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_quant8_asymm = TestModelManager::get().add("mirror_pad_one_reflect_quant8_asymm", get_test_model_one_reflect_quant8_asymm());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_quant8_asymm_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({186, 207, 186, 105, 186, 207, 127, 66, 127, 101, 127, 66, 186, 207, 186, 105, 186, 207}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // in_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({207, 186, 105, 66, 127, 101}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // placeholder4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({4}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // param9
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_quant8_asymm_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_reflect_quant8_asymm_all_inputs_as_internal", get_test_model_one_reflect_quant8_asymm_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_quant8_asymm_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({207, 186, 105, 66, 127, 101}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({186, 207, 186, 105, 186, 207, 127, 66, 127, 101, 127, 66, 186, 207, 186, 105, 186, 207}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_quant8_asymm_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_one_reflect_quant8_asymm_all_tensors_as_inputs", get_test_model_one_reflect_quant8_asymm_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({186, 207, 186, 105, 186, 207, 127, 66, 127, 101, 127, 66, 186, 207, 186, 105, 186, 207}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // in_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({207, 186, 105, 66, 127, 101}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // placeholder5
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({4}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // param10
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_reflect_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_one_reflect_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_quant8_asymm_signed() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({92, 82, 41, 22, 52, 40}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({82, 92, 82, 41, 82, 92, 52, 22, 52, 40, 52, 22, 82, 92, 82, 41, 82, 92}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_quant8_asymm_signed = TestModelManager::get().add("mirror_pad_one_reflect_quant8_asymm_signed", get_test_model_one_reflect_quant8_asymm_signed());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_quant8_asymm_signed_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({82, 92, 82, 41, 82, 92, 52, 22, 52, 40, 52, 22, 82, 92, 82, 41, 82, 92}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // in_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({92, 82, 41, 22, 52, 40}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // placeholder6
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-9}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // param11
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_quant8_asymm_signed_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_reflect_quant8_asymm_signed_all_inputs_as_internal", get_test_model_one_reflect_quant8_asymm_signed_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_quant8_asymm_signed_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({92, 82, 41, 22, 52, 40}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({82, 92, 82, 41, 82, 92, 52, 22, 52, 40, 52, 22, 82, 92, 82, 41, 82, 92}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_quant8_asymm_signed_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_one_reflect_quant8_asymm_signed_all_tensors_as_inputs", get_test_model_one_reflect_quant8_asymm_signed_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({82, 92, 82, 41, 82, 92, 52, 22, 52, 40, 52, 22, 82, 92, 82, 41, 82, 92}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // in_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({92, 82, 41, 22, 52, 40}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // placeholder7
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-9}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // param12
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_reflect_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_one_reflect_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_int32() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({25, 23, 13, 8, 15, 12}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({23, 25, 23, 13, 23, 25, 15, 8, 15, 12, 15, 8, 23, 25, 23, 13, 23, 25}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_int32 = TestModelManager::get().add("mirror_pad_one_reflect_int32", get_test_model_one_reflect_int32());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_reflect_int32_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({25, 23, 13, 8, 15, 12}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // padding
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({23, 25, 23, 13, 23, 25, 15, 8, 15, 12, 15, 8, 23, 25, 23, 13, 23, 25}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_reflect_int32_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_one_reflect_int32_all_tensors_as_inputs", get_test_model_one_reflect_int32_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({25.332655545751443f, 25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 12.61714742492535f, 22.738632088209073f, 7.7675025087889f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f, 12.148024123512428f, 15.338241641058255f, 7.7675025087889f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f, 12.148024123512428f, 15.338241641058255f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric = TestModelManager::get().add("mirror_pad_one_symmetric", get_test_model_one_symmetric());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({25.332655545751443f, 25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 12.61714742492535f, 22.738632088209073f, 7.7675025087889f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f, 12.148024123512428f, 15.338241641058255f, 7.7675025087889f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f, 12.148024123512428f, 15.338241641058255f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // in1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // placeholder8
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // param13
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_symmetric_all_inputs_as_internal", get_test_model_one_symmetric_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({25.332655545751443f, 25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 12.61714742492535f, 22.738632088209073f, 7.7675025087889f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f, 12.148024123512428f, 15.338241641058255f, 7.7675025087889f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f, 12.148024123512428f, 15.338241641058255f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_one_symmetric_all_tensors_as_inputs", get_test_model_one_symmetric_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({25.332655545751443f, 25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 12.61714742492535f, 22.738632088209073f, 7.7675025087889f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f, 12.148024123512428f, 15.338241641058255f, 7.7675025087889f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f, 12.148024123512428f, 15.338241641058255f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // in1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({25.332655545751443f, 22.738632088209073f, 12.61714742492535f, 7.7675025087889f, 15.338241641058255f, 12.148024123512428f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // placeholder9
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // param14
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_symmetric_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_one_symmetric_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_float16() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({25.33265495300293f, 25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 12.617147445678711f, 22.738632202148438f, 7.767502307891846f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f, 12.148024559020996f, 15.338241577148438f, 7.767502307891846f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f, 12.148024559020996f, 15.338241577148438f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_float16 = TestModelManager::get().add("mirror_pad_one_symmetric_float16", get_test_model_one_symmetric_float16());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_float16_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({25.33265495300293f, 25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 12.617147445678711f, 22.738632202148438f, 7.767502307891846f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f, 12.148024559020996f, 15.338241577148438f, 7.767502307891846f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f, 12.148024559020996f, 15.338241577148438f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // in1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // placeholder10
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // param15
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_float16_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_symmetric_float16_all_inputs_as_internal", get_test_model_one_symmetric_float16_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_float16_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({25.33265495300293f, 25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 12.617147445678711f, 22.738632202148438f, 7.767502307891846f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f, 12.148024559020996f, 15.338241577148438f, 7.767502307891846f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f, 12.148024559020996f, 15.338241577148438f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_float16_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_one_symmetric_float16_all_tensors_as_inputs", get_test_model_one_symmetric_float16_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_float16_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({25.33265495300293f, 25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 12.617147445678711f, 22.738632202148438f, 7.767502307891846f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f, 12.148024559020996f, 15.338241577148438f, 7.767502307891846f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f, 12.148024559020996f, 15.338241577148438f}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // in1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({25.33265495300293f, 22.738632202148438f, 12.617147445678711f, 7.767502307891846f, 15.338241577148438f, 12.148024559020996f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // placeholder11
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // param16
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_float16_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_symmetric_float16_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_one_symmetric_float16_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_quant8_asymm() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({207, 186, 105, 66, 127, 101}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({207, 207, 186, 105, 105, 186, 66, 66, 127, 101, 101, 127, 66, 66, 127, 101, 101, 127}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_quant8_asymm = TestModelManager::get().add("mirror_pad_one_symmetric_quant8_asymm", get_test_model_one_symmetric_quant8_asymm());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_quant8_asymm_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({207, 207, 186, 105, 105, 186, 66, 66, 127, 101, 101, 127, 66, 66, 127, 101, 101, 127}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // in1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({207, 186, 105, 66, 127, 101}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // placeholder12
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({4}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // param17
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_quant8_asymm_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_symmetric_quant8_asymm_all_inputs_as_internal", get_test_model_one_symmetric_quant8_asymm_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_quant8_asymm_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({207, 186, 105, 66, 127, 101}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({207, 207, 186, 105, 105, 186, 66, 66, 127, 101, 101, 127, 66, 66, 127, 101, 101, 127}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_quant8_asymm_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_one_symmetric_quant8_asymm_all_tensors_as_inputs", get_test_model_one_symmetric_quant8_asymm_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({207, 207, 186, 105, 105, 186, 66, 66, 127, 101, 101, 127, 66, 66, 127, 101, 101, 127}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // in1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({207, 186, 105, 66, 127, 101}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // placeholder13
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({4}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // param18
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_symmetric_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_one_symmetric_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_quant8_asymm_signed() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({92, 82, 41, 22, 52, 40}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({92, 92, 82, 41, 41, 82, 22, 22, 52, 40, 40, 52, 22, 22, 52, 40, 40, 52}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_quant8_asymm_signed = TestModelManager::get().add("mirror_pad_one_symmetric_quant8_asymm_signed", get_test_model_one_symmetric_quant8_asymm_signed());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_quant8_asymm_signed_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({92, 92, 82, 41, 41, 82, 22, 22, 52, 40, 40, 52, 22, 22, 52, 40, 40, 52}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // in1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({92, 82, 41, 22, 52, 40}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // placeholder14
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-9}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // param19
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_quant8_asymm_signed_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_symmetric_quant8_asymm_signed_all_inputs_as_internal", get_test_model_one_symmetric_quant8_asymm_signed_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_quant8_asymm_signed_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({92, 82, 41, 22, 52, 40}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({92, 92, 82, 41, 41, 82, 22, 22, 52, 40, 40, 52, 22, 22, 52, 40, 40, 52}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_quant8_asymm_signed_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_one_symmetric_quant8_asymm_signed_all_tensors_as_inputs", get_test_model_one_symmetric_quant8_asymm_signed_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({92, 92, 82, 41, 41, 82, 22, 22, 52, 40, 40, 52, 22, 22, 52, 40, 40, 52}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // in1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({92, 82, 41, 22, 52, 40}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // placeholder15
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-9}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // param20
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_one_symmetric_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_one_symmetric_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_int32() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({25, 23, 13, 8, 15, 12}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({25, 25, 23, 13, 13, 23, 8, 8, 15, 12, 12, 15, 8, 8, 15, 12, 12, 15}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_int32 = TestModelManager::get().add("mirror_pad_one_symmetric_int32", get_test_model_one_symmetric_int32());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_one_symmetric_int32_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({25, 23, 13, 8, 15, 12}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // padding1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 1, 1, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({25, 25, 23, 13, 13, 23, 8, 8, 15, 12, 12, 15, 8, 8, 15, 12, 12, 15}),
+ .dimensions = {3, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_one_symmetric_int32_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_one_symmetric_int32_all_tensors_as_inputs", get_test_model_one_symmetric_int32_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_reflect() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({4.030927323372037f, 25.42301210811698f, 22.91323856929842f, 7.65207077218265f, 14.863052612758228f, 13.484731943662144f, 19.547789181682887f, 23.661700534065396f, 2.815787603227047f, 0.8504242956601893f, 25.07295311759609f, 12.983012037151601f, 22.86840247373826f, 0.06318160053332078f, 13.361615821644042f, 21.646200970223475f, 6.862866638113579f, 28.358120866617668f, 27.04282372834451f, 0.9176994910066061f, 0.763375829803824f, 16.2423741838049f, 28.174474883355316f, 11.436127130646373f, 6.497981913918402f, 12.66349726748152f, 0.8712236272460383f, 6.650749988191052f, 13.136627809517162f, 14.87436724145552f, 6.992533507727179f, 6.925996246229529f}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 28.174474883355316f, 11.436127130646373f, 28.174474883355316f, 0.763375829803824f, 16.2423741838049f, 0.763375829803824f, 28.174474883355316f, 11.436127130646373f, 28.174474883355316f, 0.763375829803824f, 16.2423741838049f, 0.763375829803824f, 27.04282372834451f, 0.9176994910066061f, 27.04282372834451f, 6.862866638113579f, 28.358120866617668f, 6.862866638113579f, 27.04282372834451f, 0.9176994910066061f, 27.04282372834451f, 6.862866638113579f, 28.358120866617668f, 6.862866638113579f, 28.174474883355316f, 11.436127130646373f, 28.174474883355316f, 0.763375829803824f, 16.2423741838049f, 0.763375829803824f, 28.174474883355316f, 11.436127130646373f, 28.174474883355316f, 0.763375829803824f, 16.2423741838049f, 0.763375829803824f, 27.04282372834451f, 0.9176994910066061f, 27.04282372834451f, 6.862866638113579f, 28.358120866617668f, 6.862866638113579f, 27.04282372834451f, 0.9176994910066061f, 27.04282372834451f, 6.862866638113579f, 28.358120866617668f, 6.862866638113579f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f}),
+ .dimensions = {1, 3, 1, 3, 1, 4, 1, 4, 1, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_reflect = TestModelManager::get().add("mirror_pad_two_reflect", get_test_model_two_reflect());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_reflect_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({4.030927323372037f, 25.42301210811698f, 22.91323856929842f, 7.65207077218265f, 14.863052612758228f, 13.484731943662144f, 19.547789181682887f, 23.661700534065396f, 2.815787603227047f, 0.8504242956601893f, 25.07295311759609f, 12.983012037151601f, 22.86840247373826f, 0.06318160053332078f, 13.361615821644042f, 21.646200970223475f, 6.862866638113579f, 28.358120866617668f, 27.04282372834451f, 0.9176994910066061f, 0.763375829803824f, 16.2423741838049f, 28.174474883355316f, 11.436127130646373f, 6.497981913918402f, 12.66349726748152f, 0.8712236272460383f, 6.650749988191052f, 13.136627809517162f, 14.87436724145552f, 6.992533507727179f, 6.925996246229529f}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 28.174474883355316f, 11.436127130646373f, 28.174474883355316f, 0.763375829803824f, 16.2423741838049f, 0.763375829803824f, 28.174474883355316f, 11.436127130646373f, 28.174474883355316f, 0.763375829803824f, 16.2423741838049f, 0.763375829803824f, 27.04282372834451f, 0.9176994910066061f, 27.04282372834451f, 6.862866638113579f, 28.358120866617668f, 6.862866638113579f, 27.04282372834451f, 0.9176994910066061f, 27.04282372834451f, 6.862866638113579f, 28.358120866617668f, 6.862866638113579f, 28.174474883355316f, 11.436127130646373f, 28.174474883355316f, 0.763375829803824f, 16.2423741838049f, 0.763375829803824f, 28.174474883355316f, 11.436127130646373f, 28.174474883355316f, 0.763375829803824f, 16.2423741838049f, 0.763375829803824f, 27.04282372834451f, 0.9176994910066061f, 27.04282372834451f, 6.862866638113579f, 28.358120866617668f, 6.862866638113579f, 27.04282372834451f, 0.9176994910066061f, 27.04282372834451f, 6.862866638113579f, 28.358120866617668f, 6.862866638113579f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 6.992533507727179f, 6.925996246229529f, 6.992533507727179f, 13.136627809517162f, 14.87436724145552f, 13.136627809517162f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 0.8712236272460383f, 6.650749988191052f, 0.8712236272460383f, 6.497981913918402f, 12.66349726748152f, 6.497981913918402f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 19.547789181682887f, 23.661700534065396f, 19.547789181682887f, 14.863052612758228f, 13.484731943662144f, 14.863052612758228f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 22.91323856929842f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 4.030927323372037f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 13.361615821644042f, 21.646200970223475f, 13.361615821644042f, 22.86840247373826f, 0.06318160053332078f, 22.86840247373826f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f, 25.07295311759609f, 12.983012037151601f, 25.07295311759609f, 2.815787603227047f, 0.8504242956601893f, 2.815787603227047f}),
+ .dimensions = {1, 3, 1, 3, 1, 4, 1, 4, 1, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_reflect_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_two_reflect_all_tensors_as_inputs", get_test_model_two_reflect_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_reflect_float16() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({4.0309271812438965f, 25.423011779785156f, 22.913238525390625f, 7.652070999145508f, 14.863052368164062f, 13.484731674194336f, 19.547788619995117f, 23.661701202392578f, 2.8157875537872314f, 0.8504242897033691f, 25.072952270507812f, 12.983012199401855f, 22.8684024810791f, 0.06318160146474838f, 13.361616134643555f, 21.64620018005371f, 6.862866401672363f, 28.35811996459961f, 27.042823791503906f, 0.9176995158195496f, 0.7633758187294006f, 16.242374420166016f, 28.174474716186523f, 11.436126708984375f, 6.497982025146484f, 12.663496971130371f, 0.8712236285209656f, 6.650750160217285f, 13.136628150939941f, 14.874367713928223f, 6.9925336837768555f, 6.92599630355835f}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 28.174474716186523f, 11.436126708984375f, 28.174474716186523f, 0.7633758187294006f, 16.242374420166016f, 0.7633758187294006f, 28.174474716186523f, 11.436126708984375f, 28.174474716186523f, 0.7633758187294006f, 16.242374420166016f, 0.7633758187294006f, 27.042823791503906f, 0.9176995158195496f, 27.042823791503906f, 6.862866401672363f, 28.35811996459961f, 6.862866401672363f, 27.042823791503906f, 0.9176995158195496f, 27.042823791503906f, 6.862866401672363f, 28.35811996459961f, 6.862866401672363f, 28.174474716186523f, 11.436126708984375f, 28.174474716186523f, 0.7633758187294006f, 16.242374420166016f, 0.7633758187294006f, 28.174474716186523f, 11.436126708984375f, 28.174474716186523f, 0.7633758187294006f, 16.242374420166016f, 0.7633758187294006f, 27.042823791503906f, 0.9176995158195496f, 27.042823791503906f, 6.862866401672363f, 28.35811996459961f, 6.862866401672363f, 27.042823791503906f, 0.9176995158195496f, 27.042823791503906f, 6.862866401672363f, 28.35811996459961f, 6.862866401672363f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f}),
+ .dimensions = {1, 3, 1, 3, 1, 4, 1, 4, 1, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_reflect_float16 = TestModelManager::get().add("mirror_pad_two_reflect_float16", get_test_model_two_reflect_float16());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_reflect_float16_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({4.0309271812438965f, 25.423011779785156f, 22.913238525390625f, 7.652070999145508f, 14.863052368164062f, 13.484731674194336f, 19.547788619995117f, 23.661701202392578f, 2.8157875537872314f, 0.8504242897033691f, 25.072952270507812f, 12.983012199401855f, 22.8684024810791f, 0.06318160146474838f, 13.361616134643555f, 21.64620018005371f, 6.862866401672363f, 28.35811996459961f, 27.042823791503906f, 0.9176995158195496f, 0.7633758187294006f, 16.242374420166016f, 28.174474716186523f, 11.436126708984375f, 6.497982025146484f, 12.663496971130371f, 0.8712236285209656f, 6.650750160217285f, 13.136628150939941f, 14.874367713928223f, 6.9925336837768555f, 6.92599630355835f}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 28.174474716186523f, 11.436126708984375f, 28.174474716186523f, 0.7633758187294006f, 16.242374420166016f, 0.7633758187294006f, 28.174474716186523f, 11.436126708984375f, 28.174474716186523f, 0.7633758187294006f, 16.242374420166016f, 0.7633758187294006f, 27.042823791503906f, 0.9176995158195496f, 27.042823791503906f, 6.862866401672363f, 28.35811996459961f, 6.862866401672363f, 27.042823791503906f, 0.9176995158195496f, 27.042823791503906f, 6.862866401672363f, 28.35811996459961f, 6.862866401672363f, 28.174474716186523f, 11.436126708984375f, 28.174474716186523f, 0.7633758187294006f, 16.242374420166016f, 0.7633758187294006f, 28.174474716186523f, 11.436126708984375f, 28.174474716186523f, 0.7633758187294006f, 16.242374420166016f, 0.7633758187294006f, 27.042823791503906f, 0.9176995158195496f, 27.042823791503906f, 6.862866401672363f, 28.35811996459961f, 6.862866401672363f, 27.042823791503906f, 0.9176995158195496f, 27.042823791503906f, 6.862866401672363f, 28.35811996459961f, 6.862866401672363f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 6.9925336837768555f, 6.92599630355835f, 6.9925336837768555f, 13.136628150939941f, 14.874367713928223f, 13.136628150939941f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 0.8712236285209656f, 6.650750160217285f, 0.8712236285209656f, 6.497982025146484f, 12.663496971130371f, 6.497982025146484f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 19.547788619995117f, 23.661701202392578f, 19.547788619995117f, 14.863052368164062f, 13.484731674194336f, 14.863052368164062f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 22.913238525390625f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 4.0309271812438965f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 13.361616134643555f, 21.64620018005371f, 13.361616134643555f, 22.8684024810791f, 0.06318160146474838f, 22.8684024810791f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f, 25.072952270507812f, 12.983012199401855f, 25.072952270507812f, 2.8157875537872314f, 0.8504242897033691f, 2.8157875537872314f}),
+ .dimensions = {1, 3, 1, 3, 1, 4, 1, 4, 1, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_reflect_float16_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_two_reflect_float16_all_tensors_as_inputs", get_test_model_two_reflect_float16_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_reflect_quant8_asymm() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({36, 207, 187, 65, 123, 112, 160, 193, 27, 11, 205, 108, 187, 5, 111, 177, 59, 231, 220, 11, 10, 134, 229, 95, 56, 105, 11, 57, 109, 123, 60, 59}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27, 111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27, 160, 193, 160, 123, 112, 123, 160, 193, 160, 123, 112, 123, 187, 65, 187, 36, 207, 36, 187, 65, 187, 36, 207, 36, 160, 193, 160, 123, 112, 123, 160, 193, 160, 123, 112, 123, 187, 65, 187, 36, 207, 36, 187, 65, 187, 36, 207, 36, 111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27, 111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27, 60, 59, 60, 109, 123, 109, 60, 59, 60, 109, 123, 109, 11, 57, 11, 56, 105, 56, 11, 57, 11, 56, 105, 56, 60, 59, 60, 109, 123, 109, 60, 59, 60, 109, 123, 109, 11, 57, 11, 56, 105, 56, 11, 57, 11, 56, 105, 56, 229, 95, 229, 10, 134, 10, 229, 95, 229, 10, 134, 10, 220, 11, 220, 59, 231, 59, 220, 11, 220, 59, 231, 59, 229, 95, 229, 10, 134, 10, 229, 95, 229, 10, 134, 10, 220, 11, 220, 59, 231, 59, 220, 11, 220, 59, 231, 59, 60, 59, 60, 109, 123, 109, 60, 59, 60, 109, 123, 109, 11, 57, 11, 56, 105, 56, 11, 57, 11, 56, 105, 56, 60, 59, 60, 109, 123, 109, 60, 59, 60, 109, 123, 109, 11, 57, 11, 56, 105, 56, 11, 57, 11, 56, 105, 56, 111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27, 111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27, 160, 193, 160, 123, 112, 123, 160, 193, 160, 123, 112, 123, 187, 65, 187, 36, 207, 36, 187, 65, 187, 36, 207, 36, 160, 193, 160, 123, 112, 123, 160, 193, 160, 123, 112, 123, 187, 65, 187, 36, 207, 36, 187, 65, 187, 36, 207, 36, 111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27, 111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27}),
+ .dimensions = {1, 3, 1, 3, 1, 4, 1, 4, 1, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_reflect_quant8_asymm = TestModelManager::get().add("mirror_pad_two_reflect_quant8_asymm", get_test_model_two_reflect_quant8_asymm());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_reflect_quant8_asymm_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({36, 207, 187, 65, 123, 112, 160, 193, 27, 11, 205, 108, 187, 5, 111, 177, 59, 231, 220, 11, 10, 134, 229, 95, 56, 105, 11, 57, 109, 123, 60, 59}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27, 111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27, 160, 193, 160, 123, 112, 123, 160, 193, 160, 123, 112, 123, 187, 65, 187, 36, 207, 36, 187, 65, 187, 36, 207, 36, 160, 193, 160, 123, 112, 123, 160, 193, 160, 123, 112, 123, 187, 65, 187, 36, 207, 36, 187, 65, 187, 36, 207, 36, 111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27, 111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27, 60, 59, 60, 109, 123, 109, 60, 59, 60, 109, 123, 109, 11, 57, 11, 56, 105, 56, 11, 57, 11, 56, 105, 56, 60, 59, 60, 109, 123, 109, 60, 59, 60, 109, 123, 109, 11, 57, 11, 56, 105, 56, 11, 57, 11, 56, 105, 56, 229, 95, 229, 10, 134, 10, 229, 95, 229, 10, 134, 10, 220, 11, 220, 59, 231, 59, 220, 11, 220, 59, 231, 59, 229, 95, 229, 10, 134, 10, 229, 95, 229, 10, 134, 10, 220, 11, 220, 59, 231, 59, 220, 11, 220, 59, 231, 59, 60, 59, 60, 109, 123, 109, 60, 59, 60, 109, 123, 109, 11, 57, 11, 56, 105, 56, 11, 57, 11, 56, 105, 56, 60, 59, 60, 109, 123, 109, 60, 59, 60, 109, 123, 109, 11, 57, 11, 56, 105, 56, 11, 57, 11, 56, 105, 56, 111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27, 111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27, 160, 193, 160, 123, 112, 123, 160, 193, 160, 123, 112, 123, 187, 65, 187, 36, 207, 36, 187, 65, 187, 36, 207, 36, 160, 193, 160, 123, 112, 123, 160, 193, 160, 123, 112, 123, 187, 65, 187, 36, 207, 36, 187, 65, 187, 36, 207, 36, 111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27, 111, 177, 111, 187, 5, 187, 111, 177, 111, 187, 5, 187, 205, 108, 205, 27, 11, 27, 205, 108, 205, 27, 11, 27}),
+ .dimensions = {1, 3, 1, 3, 1, 4, 1, 4, 1, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_reflect_quant8_asymm_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_two_reflect_quant8_asymm_all_tensors_as_inputs", get_test_model_two_reflect_quant8_asymm_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_reflect_quant8_asymm_signed() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({7, 93, 83, 22, 50, 45, 69, 86, 2, -6, 91, 43, 82, -9, 44, 78, 18, 104, 99, -5, -6, 56, 104, 37, 17, 42, -6, 18, 44, 50, 19, 19}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2, 44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2, 69, 86, 69, 50, 45, 50, 69, 86, 69, 50, 45, 50, 83, 22, 83, 7, 93, 7, 83, 22, 83, 7, 93, 7, 69, 86, 69, 50, 45, 50, 69, 86, 69, 50, 45, 50, 83, 22, 83, 7, 93, 7, 83, 22, 83, 7, 93, 7, 44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2, 44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2, 19, 19, 19, 44, 50, 44, 19, 19, 19, 44, 50, 44, -6, 18, -6, 17, 42, 17, -6, 18, -6, 17, 42, 17, 19, 19, 19, 44, 50, 44, 19, 19, 19, 44, 50, 44, -6, 18, -6, 17, 42, 17, -6, 18, -6, 17, 42, 17, 104, 37, 104, -6, 56, -6, 104, 37, 104, -6, 56, -6, 99, -5, 99, 18, 104, 18, 99, -5, 99, 18, 104, 18, 104, 37, 104, -6, 56, -6, 104, 37, 104, -6, 56, -6, 99, -5, 99, 18, 104, 18, 99, -5, 99, 18, 104, 18, 19, 19, 19, 44, 50, 44, 19, 19, 19, 44, 50, 44, -6, 18, -6, 17, 42, 17, -6, 18, -6, 17, 42, 17, 19, 19, 19, 44, 50, 44, 19, 19, 19, 44, 50, 44, -6, 18, -6, 17, 42, 17, -6, 18, -6, 17, 42, 17, 44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2, 44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2, 69, 86, 69, 50, 45, 50, 69, 86, 69, 50, 45, 50, 83, 22, 83, 7, 93, 7, 83, 22, 83, 7, 93, 7, 69, 86, 69, 50, 45, 50, 69, 86, 69, 50, 45, 50, 83, 22, 83, 7, 93, 7, 83, 22, 83, 7, 93, 7, 44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2, 44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2}),
+ .dimensions = {1, 3, 1, 3, 1, 4, 1, 4, 1, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_reflect_quant8_asymm_signed = TestModelManager::get().add("mirror_pad_two_reflect_quant8_asymm_signed", get_test_model_two_reflect_quant8_asymm_signed());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_reflect_quant8_asymm_signed_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({7, 93, 83, 22, 50, 45, 69, 86, 2, -6, 91, 43, 82, -9, 44, 78, 18, 104, 99, -5, -6, 56, 104, 37, 17, 42, -6, 18, 44, 50, 19, 19}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2, 44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2, 69, 86, 69, 50, 45, 50, 69, 86, 69, 50, 45, 50, 83, 22, 83, 7, 93, 7, 83, 22, 83, 7, 93, 7, 69, 86, 69, 50, 45, 50, 69, 86, 69, 50, 45, 50, 83, 22, 83, 7, 93, 7, 83, 22, 83, 7, 93, 7, 44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2, 44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2, 19, 19, 19, 44, 50, 44, 19, 19, 19, 44, 50, 44, -6, 18, -6, 17, 42, 17, -6, 18, -6, 17, 42, 17, 19, 19, 19, 44, 50, 44, 19, 19, 19, 44, 50, 44, -6, 18, -6, 17, 42, 17, -6, 18, -6, 17, 42, 17, 104, 37, 104, -6, 56, -6, 104, 37, 104, -6, 56, -6, 99, -5, 99, 18, 104, 18, 99, -5, 99, 18, 104, 18, 104, 37, 104, -6, 56, -6, 104, 37, 104, -6, 56, -6, 99, -5, 99, 18, 104, 18, 99, -5, 99, 18, 104, 18, 19, 19, 19, 44, 50, 44, 19, 19, 19, 44, 50, 44, -6, 18, -6, 17, 42, 17, -6, 18, -6, 17, 42, 17, 19, 19, 19, 44, 50, 44, 19, 19, 19, 44, 50, 44, -6, 18, -6, 17, 42, 17, -6, 18, -6, 17, 42, 17, 44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2, 44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2, 69, 86, 69, 50, 45, 50, 69, 86, 69, 50, 45, 50, 83, 22, 83, 7, 93, 7, 83, 22, 83, 7, 93, 7, 69, 86, 69, 50, 45, 50, 69, 86, 69, 50, 45, 50, 83, 22, 83, 7, 93, 7, 83, 22, 83, 7, 93, 7, 44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2, 44, 78, 44, 82, -9, 82, 44, 78, 44, 82, -9, 82, 91, 43, 91, 2, -6, 2, 91, 43, 91, 2, -6, 2}),
+ .dimensions = {1, 3, 1, 3, 1, 4, 1, 4, 1, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_reflect_quant8_asymm_signed_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_two_reflect_quant8_asymm_signed_all_tensors_as_inputs", get_test_model_two_reflect_quant8_asymm_signed_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_reflect_int32() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({4, 25, 23, 8, 15, 13, 20, 24, 3, 1, 25, 13, 23, 0, 13, 22, 7, 28, 27, 1, 1, 16, 28, 11, 6, 13, 1, 7, 13, 15, 7, 7}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // padding2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3, 13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3, 20, 24, 20, 15, 13, 15, 20, 24, 20, 15, 13, 15, 23, 8, 23, 4, 25, 4, 23, 8, 23, 4, 25, 4, 20, 24, 20, 15, 13, 15, 20, 24, 20, 15, 13, 15, 23, 8, 23, 4, 25, 4, 23, 8, 23, 4, 25, 4, 13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3, 13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3, 7, 7, 7, 13, 15, 13, 7, 7, 7, 13, 15, 13, 1, 7, 1, 6, 13, 6, 1, 7, 1, 6, 13, 6, 7, 7, 7, 13, 15, 13, 7, 7, 7, 13, 15, 13, 1, 7, 1, 6, 13, 6, 1, 7, 1, 6, 13, 6, 28, 11, 28, 1, 16, 1, 28, 11, 28, 1, 16, 1, 27, 1, 27, 7, 28, 7, 27, 1, 27, 7, 28, 7, 28, 11, 28, 1, 16, 1, 28, 11, 28, 1, 16, 1, 27, 1, 27, 7, 28, 7, 27, 1, 27, 7, 28, 7, 7, 7, 7, 13, 15, 13, 7, 7, 7, 13, 15, 13, 1, 7, 1, 6, 13, 6, 1, 7, 1, 6, 13, 6, 7, 7, 7, 13, 15, 13, 7, 7, 7, 13, 15, 13, 1, 7, 1, 6, 13, 6, 1, 7, 1, 6, 13, 6, 13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3, 13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3, 20, 24, 20, 15, 13, 15, 20, 24, 20, 15, 13, 15, 23, 8, 23, 4, 25, 4, 23, 8, 23, 4, 25, 4, 20, 24, 20, 15, 13, 15, 20, 24, 20, 15, 13, 15, 23, 8, 23, 4, 25, 4, 23, 8, 23, 4, 25, 4, 13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3, 13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3}),
+ .dimensions = {1, 3, 1, 3, 1, 4, 1, 4, 1, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_reflect_int32 = TestModelManager::get().add("mirror_pad_two_reflect_int32", get_test_model_two_reflect_int32());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_reflect_int32_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({4, 25, 23, 8, 15, 13, 20, 24, 3, 1, 25, 13, 23, 0, 13, 22, 7, 28, 27, 1, 1, 16, 28, 11, 6, 13, 1, 7, 13, 15, 7, 7}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // padding2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3, 13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3, 20, 24, 20, 15, 13, 15, 20, 24, 20, 15, 13, 15, 23, 8, 23, 4, 25, 4, 23, 8, 23, 4, 25, 4, 20, 24, 20, 15, 13, 15, 20, 24, 20, 15, 13, 15, 23, 8, 23, 4, 25, 4, 23, 8, 23, 4, 25, 4, 13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3, 13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3, 7, 7, 7, 13, 15, 13, 7, 7, 7, 13, 15, 13, 1, 7, 1, 6, 13, 6, 1, 7, 1, 6, 13, 6, 7, 7, 7, 13, 15, 13, 7, 7, 7, 13, 15, 13, 1, 7, 1, 6, 13, 6, 1, 7, 1, 6, 13, 6, 28, 11, 28, 1, 16, 1, 28, 11, 28, 1, 16, 1, 27, 1, 27, 7, 28, 7, 27, 1, 27, 7, 28, 7, 28, 11, 28, 1, 16, 1, 28, 11, 28, 1, 16, 1, 27, 1, 27, 7, 28, 7, 27, 1, 27, 7, 28, 7, 7, 7, 7, 13, 15, 13, 7, 7, 7, 13, 15, 13, 1, 7, 1, 6, 13, 6, 1, 7, 1, 6, 13, 6, 7, 7, 7, 13, 15, 13, 7, 7, 7, 13, 15, 13, 1, 7, 1, 6, 13, 6, 1, 7, 1, 6, 13, 6, 13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3, 13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3, 20, 24, 20, 15, 13, 15, 20, 24, 20, 15, 13, 15, 23, 8, 23, 4, 25, 4, 23, 8, 23, 4, 25, 4, 20, 24, 20, 15, 13, 15, 20, 24, 20, 15, 13, 15, 23, 8, 23, 4, 25, 4, 23, 8, 23, 4, 25, 4, 13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3, 13, 22, 13, 23, 0, 23, 13, 22, 13, 23, 0, 23, 25, 13, 25, 3, 1, 3, 25, 13, 25, 3, 1, 3}),
+ .dimensions = {1, 3, 1, 3, 1, 4, 1, 4, 1, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_reflect_int32_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_two_reflect_int32_all_tensors_as_inputs", get_test_model_two_reflect_int32_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_symmetric() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({4.030927323372037f, 25.42301210811698f, 22.91323856929842f, 7.65207077218265f, 14.863052612758228f, 13.484731943662144f, 19.547789181682887f, 23.661700534065396f, 2.815787603227047f, 0.8504242956601893f, 25.07295311759609f, 12.983012037151601f, 22.86840247373826f, 0.06318160053332078f, 13.361615821644042f, 21.646200970223475f, 6.862866638113579f, 28.358120866617668f, 27.04282372834451f, 0.9176994910066061f, 0.763375829803824f, 16.2423741838049f, 28.174474883355316f, 11.436127130646373f, 6.497981913918402f, 12.66349726748152f, 0.8712236272460383f, 6.650749988191052f, 13.136627809517162f, 14.87436724145552f, 6.992533507727179f, 6.925996246229529f}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 2, 1, 1, 2, 1, 0, 1, 0, 2}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 25.42301210811698f, 4.030927323372037f, 4.030927323372037f, 25.42301210811698f, 25.42301210811698f, 4.030927323372037f, 4.030927323372037f, 25.42301210811698f, 25.42301210811698f, 4.030927323372037f, 4.030927323372037f, 25.42301210811698f, 25.42301210811698f, 4.030927323372037f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 25.42301210811698f, 4.030927323372037f, 4.030927323372037f, 25.42301210811698f, 25.42301210811698f, 4.030927323372037f, 4.030927323372037f, 25.42301210811698f, 25.42301210811698f, 4.030927323372037f, 4.030927323372037f, 25.42301210811698f, 25.42301210811698f, 4.030927323372037f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 25.42301210811698f, 4.030927323372037f, 4.030927323372037f, 25.42301210811698f, 25.42301210811698f, 4.030927323372037f, 4.030927323372037f, 25.42301210811698f, 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+ .dimensions = {1, 3, 2, 3, 2, 5, 3, 5, 2, 4},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_symmetric = TestModelManager::get().add("mirror_pad_two_symmetric", get_test_model_two_symmetric());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_symmetric_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({4.030927323372037f, 25.42301210811698f, 22.91323856929842f, 7.65207077218265f, 14.863052612758228f, 13.484731943662144f, 19.547789181682887f, 23.661700534065396f, 2.815787603227047f, 0.8504242956601893f, 25.07295311759609f, 12.983012037151601f, 22.86840247373826f, 0.06318160053332078f, 13.361615821644042f, 21.646200970223475f, 6.862866638113579f, 28.358120866617668f, 27.04282372834451f, 0.9176994910066061f, 0.763375829803824f, 16.2423741838049f, 28.174474883355316f, 11.436127130646373f, 6.497981913918402f, 12.66349726748152f, 0.8712236272460383f, 6.650749988191052f, 13.136627809517162f, 14.87436724145552f, 6.992533507727179f, 6.925996246229529f}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 2, 1, 1, 2, 1, 0, 1, 0, 2}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 4.030927323372037f, 25.42301210811698f, 25.42301210811698f, 4.030927323372037f, 4.030927323372037f, 25.42301210811698f, 25.42301210811698f, 4.030927323372037f, 4.030927323372037f, 25.42301210811698f, 25.42301210811698f, 4.030927323372037f, 4.030927323372037f, 25.42301210811698f, 25.42301210811698f, 4.030927323372037f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 22.91323856929842f, 7.65207077218265f, 7.65207077218265f, 22.91323856929842f, 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+ .dimensions = {1, 3, 2, 3, 2, 5, 3, 5, 2, 4},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_symmetric_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_two_symmetric_all_tensors_as_inputs", get_test_model_two_symmetric_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_symmetric_float16() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({4.0309271812438965f, 25.423011779785156f, 22.913238525390625f, 7.652070999145508f, 14.863052368164062f, 13.484731674194336f, 19.547788619995117f, 23.661701202392578f, 2.8157875537872314f, 0.8504242897033691f, 25.072952270507812f, 12.983012199401855f, 22.8684024810791f, 0.06318160146474838f, 13.361616134643555f, 21.64620018005371f, 6.862866401672363f, 28.35811996459961f, 27.042823791503906f, 0.9176995158195496f, 0.7633758187294006f, 16.242374420166016f, 28.174474716186523f, 11.436126708984375f, 6.497982025146484f, 12.663496971130371f, 0.8712236285209656f, 6.650750160217285f, 13.136628150939941f, 14.874367713928223f, 6.9925336837768555f, 6.92599630355835f}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 2, 1, 1, 2, 1, 0, 1, 0, 2}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({22.913238525390625f, 7.652070999145508f, 7.652070999145508f, 22.913238525390625f, 22.913238525390625f, 7.652070999145508f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 25.423011779785156f, 4.0309271812438965f, 4.0309271812438965f, 25.423011779785156f, 25.423011779785156f, 4.0309271812438965f, 4.0309271812438965f, 25.423011779785156f, 25.423011779785156f, 4.0309271812438965f, 4.0309271812438965f, 25.423011779785156f, 25.423011779785156f, 4.0309271812438965f, 22.913238525390625f, 7.652070999145508f, 7.652070999145508f, 22.913238525390625f, 22.913238525390625f, 7.652070999145508f, 7.652070999145508f, 22.913238525390625f, 22.913238525390625f, 7.652070999145508f, 7.652070999145508f, 22.913238525390625f, 22.913238525390625f, 7.652070999145508f, 7.652070999145508f, 22.913238525390625f, 22.913238525390625f, 7.652070999145508f, 7.652070999145508f, 22.913238525390625f, 22.913238525390625f, 7.652070999145508f, 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12.663496971130371f, 12.663496971130371f, 6.497982025146484f, 6.497982025146484f, 12.663496971130371f, 12.663496971130371f, 6.497982025146484f, 0.8712236285209656f, 6.650750160217285f, 6.650750160217285f, 0.8712236285209656f, 0.8712236285209656f, 6.650750160217285f, 6.650750160217285f, 0.8712236285209656f, 0.8712236285209656f, 6.650750160217285f, 6.650750160217285f, 0.8712236285209656f, 0.8712236285209656f, 6.650750160217285f, 6.650750160217285f, 0.8712236285209656f}),
+ .dimensions = {1, 3, 2, 3, 2, 5, 3, 5, 2, 4},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_symmetric_float16 = TestModelManager::get().add("mirror_pad_two_symmetric_float16", get_test_model_two_symmetric_float16());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_symmetric_float16_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({4.0309271812438965f, 25.423011779785156f, 22.913238525390625f, 7.652070999145508f, 14.863052368164062f, 13.484731674194336f, 19.547788619995117f, 23.661701202392578f, 2.8157875537872314f, 0.8504242897033691f, 25.072952270507812f, 12.983012199401855f, 22.8684024810791f, 0.06318160146474838f, 13.361616134643555f, 21.64620018005371f, 6.862866401672363f, 28.35811996459961f, 27.042823791503906f, 0.9176995158195496f, 0.7633758187294006f, 16.242374420166016f, 28.174474716186523f, 11.436126708984375f, 6.497982025146484f, 12.663496971130371f, 0.8712236285209656f, 6.650750160217285f, 13.136628150939941f, 14.874367713928223f, 6.9925336837768555f, 6.92599630355835f}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 2, 1, 1, 2, 1, 0, 1, 0, 2}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({22.913238525390625f, 7.652070999145508f, 7.652070999145508f, 22.913238525390625f, 22.913238525390625f, 7.652070999145508f, 7.652070999145508f, 22.913238525390625f, 4.0309271812438965f, 25.423011779785156f, 25.423011779785156f, 4.0309271812438965f, 4.0309271812438965f, 25.423011779785156f, 25.423011779785156f, 4.0309271812438965f, 4.0309271812438965f, 25.423011779785156f, 25.423011779785156f, 4.0309271812438965f, 4.0309271812438965f, 25.423011779785156f, 25.423011779785156f, 4.0309271812438965f, 22.913238525390625f, 7.652070999145508f, 7.652070999145508f, 22.913238525390625f, 22.913238525390625f, 7.652070999145508f, 7.652070999145508f, 22.913238525390625f, 22.913238525390625f, 7.652070999145508f, 7.652070999145508f, 22.913238525390625f, 22.913238525390625f, 7.652070999145508f, 7.652070999145508f, 22.913238525390625f, 22.913238525390625f, 7.652070999145508f, 7.652070999145508f, 22.913238525390625f, 22.913238525390625f, 7.652070999145508f, 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+ .dimensions = {1, 3, 2, 3, 2, 5, 3, 5, 2, 4},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_symmetric_float16_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_two_symmetric_float16_all_tensors_as_inputs", get_test_model_two_symmetric_float16_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_symmetric_quant8_asymm() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({36, 207, 187, 65, 123, 112, 160, 193, 27, 11, 205, 108, 187, 5, 111, 177, 59, 231, 220, 11, 10, 134, 229, 95, 56, 105, 11, 57, 109, 123, 60, 59}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 2, 1, 1, 2, 1, 0, 1, 0, 2}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({187, 65, 65, 187, 187, 65, 65, 187, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 160, 193, 193, 160, 160, 193, 193, 160, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 123, 112, 112, 123, 123, 112, 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56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11}),
+ .dimensions = {1, 3, 2, 3, 2, 5, 3, 5, 2, 4},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_symmetric_quant8_asymm = TestModelManager::get().add("mirror_pad_two_symmetric_quant8_asymm", get_test_model_two_symmetric_quant8_asymm());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_symmetric_quant8_asymm_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({36, 207, 187, 65, 123, 112, 160, 193, 27, 11, 205, 108, 187, 5, 111, 177, 59, 231, 220, 11, 10, 134, 229, 95, 56, 105, 11, 57, 109, 123, 60, 59}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 2, 1, 1, 2, 1, 0, 1, 0, 2}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({187, 65, 65, 187, 187, 65, 65, 187, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 36, 207, 207, 36, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 187, 65, 65, 187, 160, 193, 193, 160, 160, 193, 193, 160, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 123, 112, 112, 123, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 160, 193, 193, 160, 123, 112, 112, 123, 123, 112, 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59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 11, 57, 57, 11, 11, 57, 57, 11, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 60, 59, 59, 60, 60, 59, 59, 60, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 109, 123, 123, 109, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 60, 59, 59, 60, 11, 57, 57, 11, 11, 57, 57, 11, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 56, 105, 105, 56, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11, 11, 57, 57, 11}),
+ .dimensions = {1, 3, 2, 3, 2, 5, 3, 5, 2, 4},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_symmetric_quant8_asymm_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_two_symmetric_quant8_asymm_all_tensors_as_inputs", get_test_model_two_symmetric_quant8_asymm_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_symmetric_quant8_asymm_signed() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({7, 93, 83, 22, 50, 45, 69, 86, 2, -6, 91, 43, 82, -9, 44, 78, 18, 104, 99, -5, -6, 56, 104, 37, 17, 42, -6, 18, 44, 50, 19, 19}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 2, 1, 1, 2, 1, 0, 1, 0, 2}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 50, 45, 45, 50, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 69, 86, 86, 69, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 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+ .dimensions = {1, 3, 2, 3, 2, 5, 3, 5, 2, 4},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_symmetric_quant8_asymm_signed = TestModelManager::get().add("mirror_pad_two_symmetric_quant8_asymm_signed", get_test_model_two_symmetric_quant8_asymm_signed());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_symmetric_quant8_asymm_signed_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({7, 93, 83, 22, 50, 45, 69, 86, 2, -6, 91, 43, 82, -9, 44, 78, 18, 104, 99, -5, -6, 56, 104, 37, 17, 42, -6, 18, 44, 50, 19, 19}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 2, 1, 1, 2, 1, 0, 1, 0, 2}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 7, 93, 93, 7, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 83, 22, 22, 83, 69, 86, 86, 69, 69, 86, 86, 69, 50, 45, 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+ .dimensions = {1, 3, 2, 3, 2, 5, 3, 5, 2, 4},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_symmetric_quant8_asymm_signed_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_two_symmetric_quant8_asymm_signed_all_tensors_as_inputs", get_test_model_two_symmetric_quant8_asymm_signed_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_symmetric_int32() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({4, 25, 23, 8, 15, 13, 20, 24, 3, 1, 25, 13, 23, 0, 13, 22, 7, 28, 27, 1, 1, 16, 28, 11, 6, 13, 1, 7, 13, 15, 7, 7}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // padding3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 2, 1, 1, 2, 1, 0, 1, 0, 2}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 25, 13, 13, 25, 25, 13, 13, 25, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 13, 22, 22, 13, 13, 22, 22, 13, 23, 0, 0, 23, 23, 0, 0, 23, 23, 0, 0, 23, 23, 0, 0, 23, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 23, 0, 0, 23, 23, 0, 0, 23, 23, 0, 0, 23, 23, 0, 0, 23, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 23, 0, 0, 23, 23, 0, 0, 23, 23, 0, 0, 23, 23, 0, 0, 23, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 23, 0, 0, 23, 23, 0, 0, 23, 23, 0, 0, 23, 23, 0, 0, 23, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 23, 0, 0, 23, 23, 0, 0, 23, 23, 0, 0, 23, 23, 0, 0, 23, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 23, 0, 0, 23, 23, 0, 0, 23, 23, 0, 0, 23, 23, 0, 0, 23, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 13, 22, 22, 13, 25, 13, 13, 25, 25, 13, 13, 25, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 3, 1, 1, 3, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 13, 13, 25, 25, 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7, 7, 7, 7, 7, 7, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 1, 7, 7, 1, 1, 7, 7, 1, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 7, 7, 7, 7, 7, 7, 7, 7, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 1, 7, 7, 1, 1, 7, 7, 1, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1}),
+ .dimensions = {1, 3, 2, 3, 2, 5, 3, 5, 2, 4},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_symmetric_int32 = TestModelManager::get().add("mirror_pad_two_symmetric_int32", get_test_model_two_symmetric_int32());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_two_symmetric_int32_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({4, 25, 23, 8, 15, 13, 20, 24, 3, 1, 25, 13, 23, 0, 13, 22, 7, 28, 27, 1, 1, 16, 28, 11, 6, 13, 1, 7, 13, 15, 7, 7}),
+ .dimensions = {1, 2, 1, 2, 1, 2, 1, 2, 1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // padding3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 2, 1, 1, 2, 1, 0, 1, 0, 2}),
+ .dimensions = {10, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 15, 13, 13, 15, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 20, 24, 24, 20, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 23, 8, 8, 23, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 4, 25, 25, 4, 23, 8, 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7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 6, 13, 13, 6, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1, 1, 7, 7, 1}),
+ .dimensions = {1, 3, 2, 3, 2, 5, 3, 5, 2, 4},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_two_symmetric_int32_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_two_symmetric_int32_all_tensors_as_inputs", get_test_model_two_symmetric_int32_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({28.68102815667748f, 28.43482461178048f, 1.6965410318042606f, 2.546159854767649f, 25.064966343883487f, 22.079099672055698f, 20.091912043206626f, 9.244093727674326f, 18.178324970353874f, 18.204052009225137f, 17.43612051336009f, 4.751486107644167f, 12.920089208738059f, 11.80595460616114f, 21.690362437123976f, 29.84458688849228f, 28.481864192797307f, 16.325311422879626f, 13.345625661775607f, 8.047222249479843f, 1.0777298817857284f, 0.8233457127245702f, 13.946815862919363f, 9.553953835610322f, 11.400447657021349f, 26.75368373484862f, 15.772583074380849f, 16.815310830794967f, 7.083702213451862f, 0.7157423742234659f, 9.7542878628348f, 4.1009217895939996f, 15.306715375116035f, 29.96050704577656f, 20.234390920376104f, 5.455304904694332f, 26.807146097489653f, 23.902797642649187f, 22.03205075681933f, 27.19780949692683f, 22.88656451499213f, 23.692429123852897f, 10.613609335248105f, 29.429297192163798f, 28.857028136946774f, 4.835539599120566f, 22.620122149556163f, 21.454526947123604f, 13.84220093225933f, 15.91067148370335f, 14.70041765550574f, 27.74496216283711f, 15.025231878919646f, 24.945734693754368f, 10.617726146061477f, 26.485527557437592f, 26.991017662698773f, 13.83036494644913f, 17.03115211260733f, 27.609913175757864f, 21.71318861616055f, 14.598256645847552f, 6.654330329730326f, 9.74001731306694f, 20.987149142107306f, 4.9820905648237845f, 27.238214898782836f, 8.04412538699449f, 27.341335076041403f, 9.286893748483822f, 28.72085134668474f, 21.18617419102814f, 15.127464509499527f, 15.532432684456563f, 19.542431969003722f, 17.638341353834537f, 9.355329736530006f, 6.234554236137817f, 15.356749750658475f, 28.02463077401336f, 18.69795260177617f, 2.2612610722213624f, 24.611999841360507f, 21.778478624318943f, 27.229608628539626f, 5.742081999123525f, 22.343481728320626f, 1.7627668919596717f, 19.58729782303649f, 8.19299197011448f, 6.798495877342892f, 26.264735143447137f, 3.1879794793657465f, 15.670879960767898f, 25.61829021554616f, 7.344959339070507f, 6.314368160869394f, 26.4174527809884f, 12.687529451690882f, 21.50883296714926f, 0.9561921038023535f, 10.870707339097219f, 5.156429763771971f, 20.182963242406252f, 2.4870953221372663f, 28.63686496037243f, 0.7603414448070311f, 21.88270522325412f, 0.6343460916945198f, 7.670701621723278f, 24.400631622068275f, 4.713548660603247f, 5.512164277529285f, 20.744862780407722f, 11.566976440576816f, 1.2948298739249797f, 29.700046386084033f, 4.542603262696546f, 1.0880698273024203f, 10.32603016610384f, 18.457184499745726f, 22.27378869377339f, 3.3934470905423075f, 10.116413195899357f, 0.9243257288006568f, 13.45959787476882f, 22.979098097642343f, 22.198399911621014f, 27.060604750501103f, 22.669864610251928f, 25.873373289762835f, 21.160354201522967f, 14.18338536294938f, 6.7658271104366285f, 19.824854959710414f, 9.489177801847775f, 3.0614731514909463f, 13.434655842574534f, 26.24289124043902f, 3.826093938563636f, 17.54867094331822f, 11.78857650315502f, 15.444080902925313f, 4.314883919308318f, 28.791935594614824f, 7.772892697566165f, 18.182338171605082f, 12.592666369672408f, 0.5409965737477984f, 16.7385037151724f, 4.217081368840027f, 1.703429874695892f, 1.0066873874594084f, 4.834950455437025f, 2.8761583089954956f, 19.052270926160006f, 15.24777552106931f, 29.503982821425833f, 28.0239095609042f, 29.835756997785094f, 6.974215220034302f, 13.340923653590902f, 7.523422855234715f, 17.73712036643994f, 18.72492152264347f, 24.00622366903189f, 21.28494911488049f, 7.69827865464105f, 12.690507682875648f, 15.785698313417537f, 0.1447434316088514f, 1.0649823512329382f, 12.261792531662229f, 3.33524901689928f, 21.71309018607915f, 7.225965433249898f, 2.993192602649729f, 5.452802349012758f, 6.9457628813142245f, 6.5206090415507765f, 15.622090921436925f, 13.932093334315208f, 9.29178212632239f, 19.25276273042024f, 6.373492259834692f, 27.196880301950472f, 28.89349964487713f, 21.867931367325728f, 13.01201606368995f, 15.34504026651143f, 17.432289181204784f, 1.5370423081749007f, 12.54049165447369f, 15.751935969592854f, 5.436751824755146f, 2.81360365374955f, 24.07965626116158f, 10.985518996301938f, 15.576290702969565f, 27.643510427756077f, 18.31531011309091f, 8.687423025904899f, 29.50563220659956f, 11.166801298024023f, 0.5716531442881378f, 20.559320169446085f, 3.0348562683947042f, 9.177670821187947f, 25.218350613565224f, 20.17715263934298f, 0.4716621664301457f, 13.54270377605947f, 12.320231267205209f, 14.575888320060034f, 6.2474068007339305f, 17.66235186462625f, 2.213679404257589f, 8.530780529411576f, 11.187063151409038f, 28.05811302145533f, 2.2964466108006087f, 22.64952342743696f, 5.770773839004716f, 17.146582239879926f, 11.753429110927433f, 13.896731467470222f, 22.60741517207155f, 11.851276804735885f, 3.6518844040100875f, 3.6531029916461986f, 2.4153215326088953f, 25.502126217145438f, 19.22974781493195f, 28.790056901874365f, 20.779576399639488f, 0.7400631796230317f, 19.77478991531755f, 23.31635803949396f, 21.70554839949389f, 14.938485612888524f, 10.727538531929156f, 13.71107141855355f, 23.961662510390394f, 8.068274814829577f, 15.789112344189004f, 14.326786261695656f, 28.640905408839924f, 24.13049930758013f, 27.961615806547155f, 25.080167207171822f, 8.90291006744023f, 6.948820834547174f, 14.663684203450902f, 7.782160240835196f, 12.829614958677857f, 20.374206460834465f, 27.557406816850055f, 17.577017410353022f, 24.5355976169745f, 2.8784193257599746f, 10.681716839105125f, 29.93244064120892f, 4.395031438686942f, 12.503041304246661f, 2.0051818635844842f, 2.58448069796698f, 26.86501056284191f, 29.659110861229273f, 19.44246233349408f, 3.8554501475203007f, 8.891475585980874f, 6.950989300400724f, 20.12196977849825f, 20.43297022493511f, 13.165375107347339f, 15.719843049419296f, 3.362107907835723f, 16.22679747343502f, 28.498161651684075f, 22.673319076830868f, 2.8846338381268732f, 15.495040844813204f, 21.46094452906384f, 7.717815526477821f, 26.846899499932935f, 13.828228923839157f, 21.096936293195274f, 12.12490168388222f, 29.853991126690776f, 23.484472132698677f, 17.203212021795913f, 4.342950686810733f, 13.235497784361648f, 0.8815472892817433f, 17.854925256204158f, 26.454525531102696f, 5.412734760237447f, 15.30514509683229f, 14.47374975844103f, 12.147440371004084f, 21.31380239082444f, 28.10009756955776f, 21.161776106341588f, 14.174975386285801f, 28.859322342480255f, 9.921825017018518f, 22.368382642858155f, 19.75455077322128f, 22.84826624833346f, 25.562196834189272f, 6.749966412675641f, 18.637470868500102f, 12.08171654111675f, 20.009156402026626f, 29.31702193936783f, 19.04492540247065f, 0.34817382237329f, 13.936464233005035f, 21.347294503460798f, 26.496628105560152f, 19.502550999232113f, 24.482097050792696f, 0.5141218907210998f, 28.296886954425393f, 21.883909009978364f, 18.193318557542334f, 27.15969090510142f, 26.54039181156207f, 3.013721419122252f, 24.468636488405615f, 23.01002222335158f, 5.986141400279795f, 22.327370775055996f, 17.586823310007755f, 5.744832714603162f, 24.12568187980187f, 4.136193843592172f, 18.369711193150856f, 13.031939524871754f, 7.610733325803549f, 16.9828386992738f, 14.01260637776116f, 6.149924838331157f, 29.003423622286192f, 2.1847610213393587f, 0.09111864246665768f, 14.562693878970936f, 25.11574491912604f, 19.75206190320358f, 22.6400876622412f, 14.550013599902703f, 20.24407064666962f, 10.046719117307441f, 8.00835792962951f, 15.087021245134029f, 0.8258344949231056f, 2.3942576974966645f, 22.618792209245914f, 5.210989138399996f, 22.50767177459249f}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({23.01002222335158f, 23.01002222335158f, 5.986141400279795f, 22.327370775055996f, 17.586823310007755f, 5.744832714603162f, 24.12568187980187f, 24.12568187980187f, 23.01002222335158f, 23.01002222335158f, 5.986141400279795f, 22.327370775055996f, 17.586823310007755f, 5.744832714603162f, 24.12568187980187f, 24.12568187980187f, 4.136193843592172f, 4.136193843592172f, 18.369711193150856f, 13.031939524871754f, 7.610733325803549f, 16.9828386992738f, 14.01260637776116f, 14.01260637776116f, 6.149924838331157f, 6.149924838331157f, 29.003423622286192f, 2.1847610213393587f, 0.09111864246665768f, 14.562693878970936f, 25.11574491912604f, 25.11574491912604f, 19.75206190320358f, 19.75206190320358f, 22.6400876622412f, 14.550013599902703f, 20.24407064666962f, 10.046719117307441f, 8.00835792962951f, 8.00835792962951f, 15.087021245134029f, 15.087021245134029f, 0.8258344949231056f, 2.3942576974966645f, 22.618792209245914f, 5.210989138399996f, 22.50767177459249f, 22.50767177459249f, 15.087021245134029f, 15.087021245134029f, 0.8258344949231056f, 2.3942576974966645f, 22.618792209245914f, 5.210989138399996f, 22.50767177459249f, 22.50767177459249f, 19.75206190320358f, 19.75206190320358f, 22.6400876622412f, 14.550013599902703f, 20.24407064666962f, 10.046719117307441f, 8.00835792962951f, 8.00835792962951f, 6.149924838331157f, 6.149924838331157f, 29.003423622286192f, 2.1847610213393587f, 0.09111864246665768f, 14.562693878970936f, 25.11574491912604f, 25.11574491912604f, 4.136193843592172f, 4.136193843592172f, 18.369711193150856f, 13.031939524871754f, 7.610733325803549f, 16.9828386992738f, 14.01260637776116f, 14.01260637776116f, 23.01002222335158f, 23.01002222335158f, 5.986141400279795f, 22.327370775055996f, 17.586823310007755f, 5.744832714603162f, 24.12568187980187f, 24.12568187980187f, 21.31380239082444f, 21.31380239082444f, 28.10009756955776f, 21.161776106341588f, 14.174975386285801f, 28.859322342480255f, 9.921825017018518f, 9.921825017018518f, 21.31380239082444f, 21.31380239082444f, 28.10009756955776f, 21.161776106341588f, 14.174975386285801f, 28.859322342480255f, 9.921825017018518f, 9.921825017018518f, 22.368382642858155f, 22.368382642858155f, 19.75455077322128f, 22.84826624833346f, 25.562196834189272f, 6.749966412675641f, 18.637470868500102f, 18.637470868500102f, 12.08171654111675f, 12.08171654111675f, 20.009156402026626f, 29.31702193936783f, 19.04492540247065f, 0.34817382237329f, 13.936464233005035f, 13.936464233005035f, 21.347294503460798f, 21.347294503460798f, 26.496628105560152f, 19.502550999232113f, 24.482097050792696f, 0.5141218907210998f, 28.296886954425393f, 28.296886954425393f, 21.883909009978364f, 21.883909009978364f, 18.193318557542334f, 27.15969090510142f, 26.54039181156207f, 3.013721419122252f, 24.468636488405615f, 24.468636488405615f, 21.883909009978364f, 21.883909009978364f, 18.193318557542334f, 27.15969090510142f, 26.54039181156207f, 3.013721419122252f, 24.468636488405615f, 24.468636488405615f, 21.347294503460798f, 21.347294503460798f, 26.496628105560152f, 19.502550999232113f, 24.482097050792696f, 0.5141218907210998f, 28.296886954425393f, 28.296886954425393f, 12.08171654111675f, 12.08171654111675f, 20.009156402026626f, 29.31702193936783f, 19.04492540247065f, 0.34817382237329f, 13.936464233005035f, 13.936464233005035f, 22.368382642858155f, 22.368382642858155f, 19.75455077322128f, 22.84826624833346f, 25.562196834189272f, 6.749966412675641f, 18.637470868500102f, 18.637470868500102f, 21.31380239082444f, 21.31380239082444f, 28.10009756955776f, 21.161776106341588f, 14.174975386285801f, 28.859322342480255f, 9.921825017018518f, 9.921825017018518f, 8.891475585980874f, 8.891475585980874f, 6.950989300400724f, 20.12196977849825f, 20.43297022493511f, 13.165375107347339f, 15.719843049419296f, 15.719843049419296f, 8.891475585980874f, 8.891475585980874f, 6.950989300400724f, 20.12196977849825f, 20.43297022493511f, 13.165375107347339f, 15.719843049419296f, 15.719843049419296f, 3.362107907835723f, 3.362107907835723f, 16.22679747343502f, 28.498161651684075f, 22.673319076830868f, 2.8846338381268732f, 15.495040844813204f, 15.495040844813204f, 21.46094452906384f, 21.46094452906384f, 7.717815526477821f, 26.846899499932935f, 13.828228923839157f, 21.096936293195274f, 12.12490168388222f, 12.12490168388222f, 29.853991126690776f, 29.853991126690776f, 23.484472132698677f, 17.203212021795913f, 4.342950686810733f, 13.235497784361648f, 0.8815472892817433f, 0.8815472892817433f, 17.854925256204158f, 17.854925256204158f, 26.454525531102696f, 5.412734760237447f, 15.30514509683229f, 14.47374975844103f, 12.147440371004084f, 12.147440371004084f, 17.854925256204158f, 17.854925256204158f, 26.454525531102696f, 5.412734760237447f, 15.30514509683229f, 14.47374975844103f, 12.147440371004084f, 12.147440371004084f, 29.853991126690776f, 29.853991126690776f, 23.484472132698677f, 17.203212021795913f, 4.342950686810733f, 13.235497784361648f, 0.8815472892817433f, 0.8815472892817433f, 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4.9820905648237845f}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric = TestModelManager::get().add("mirror_pad_three_symmetric", get_test_model_three_symmetric());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({23.01002222335158f, 23.01002222335158f, 5.986141400279795f, 22.327370775055996f, 17.586823310007755f, 5.744832714603162f, 24.12568187980187f, 24.12568187980187f, 23.01002222335158f, 23.01002222335158f, 5.986141400279795f, 22.327370775055996f, 17.586823310007755f, 5.744832714603162f, 24.12568187980187f, 24.12568187980187f, 4.136193843592172f, 4.136193843592172f, 18.369711193150856f, 13.031939524871754f, 7.610733325803549f, 16.9828386992738f, 14.01260637776116f, 14.01260637776116f, 6.149924838331157f, 6.149924838331157f, 29.003423622286192f, 2.1847610213393587f, 0.09111864246665768f, 14.562693878970936f, 25.11574491912604f, 25.11574491912604f, 19.75206190320358f, 19.75206190320358f, 22.6400876622412f, 14.550013599902703f, 20.24407064666962f, 10.046719117307441f, 8.00835792962951f, 8.00835792962951f, 15.087021245134029f, 15.087021245134029f, 0.8258344949231056f, 2.3942576974966645f, 22.618792209245914f, 5.210989138399996f, 22.50767177459249f, 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4.9820905648237845f}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // in4_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({28.68102815667748f, 28.43482461178048f, 1.6965410318042606f, 2.546159854767649f, 25.064966343883487f, 22.079099672055698f, 20.091912043206626f, 9.244093727674326f, 18.178324970353874f, 18.204052009225137f, 17.43612051336009f, 4.751486107644167f, 12.920089208738059f, 11.80595460616114f, 21.690362437123976f, 29.84458688849228f, 28.481864192797307f, 16.325311422879626f, 13.345625661775607f, 8.047222249479843f, 1.0777298817857284f, 0.8233457127245702f, 13.946815862919363f, 9.553953835610322f, 11.400447657021349f, 26.75368373484862f, 15.772583074380849f, 16.815310830794967f, 7.083702213451862f, 0.7157423742234659f, 9.7542878628348f, 4.1009217895939996f, 15.306715375116035f, 29.96050704577656f, 20.234390920376104f, 5.455304904694332f, 26.807146097489653f, 23.902797642649187f, 22.03205075681933f, 27.19780949692683f, 22.88656451499213f, 23.692429123852897f, 10.613609335248105f, 29.429297192163798f, 28.857028136946774f, 4.835539599120566f, 22.620122149556163f, 21.454526947123604f, 13.84220093225933f, 15.91067148370335f, 14.70041765550574f, 27.74496216283711f, 15.025231878919646f, 24.945734693754368f, 10.617726146061477f, 26.485527557437592f, 26.991017662698773f, 13.83036494644913f, 17.03115211260733f, 27.609913175757864f, 21.71318861616055f, 14.598256645847552f, 6.654330329730326f, 9.74001731306694f, 20.987149142107306f, 4.9820905648237845f, 27.238214898782836f, 8.04412538699449f, 27.341335076041403f, 9.286893748483822f, 28.72085134668474f, 21.18617419102814f, 15.127464509499527f, 15.532432684456563f, 19.542431969003722f, 17.638341353834537f, 9.355329736530006f, 6.234554236137817f, 15.356749750658475f, 28.02463077401336f, 18.69795260177617f, 2.2612610722213624f, 24.611999841360507f, 21.778478624318943f, 27.229608628539626f, 5.742081999123525f, 22.343481728320626f, 1.7627668919596717f, 19.58729782303649f, 8.19299197011448f, 6.798495877342892f, 26.264735143447137f, 3.1879794793657465f, 15.670879960767898f, 25.61829021554616f, 7.344959339070507f, 6.314368160869394f, 26.4174527809884f, 12.687529451690882f, 21.50883296714926f, 0.9561921038023535f, 10.870707339097219f, 5.156429763771971f, 20.182963242406252f, 2.4870953221372663f, 28.63686496037243f, 0.7603414448070311f, 21.88270522325412f, 0.6343460916945198f, 7.670701621723278f, 24.400631622068275f, 4.713548660603247f, 5.512164277529285f, 20.744862780407722f, 11.566976440576816f, 1.2948298739249797f, 29.700046386084033f, 4.542603262696546f, 1.0880698273024203f, 10.32603016610384f, 18.457184499745726f, 22.27378869377339f, 3.3934470905423075f, 10.116413195899357f, 0.9243257288006568f, 13.45959787476882f, 22.979098097642343f, 22.198399911621014f, 27.060604750501103f, 22.669864610251928f, 25.873373289762835f, 21.160354201522967f, 14.18338536294938f, 6.7658271104366285f, 19.824854959710414f, 9.489177801847775f, 3.0614731514909463f, 13.434655842574534f, 26.24289124043902f, 3.826093938563636f, 17.54867094331822f, 11.78857650315502f, 15.444080902925313f, 4.314883919308318f, 28.791935594614824f, 7.772892697566165f, 18.182338171605082f, 12.592666369672408f, 0.5409965737477984f, 16.7385037151724f, 4.217081368840027f, 1.703429874695892f, 1.0066873874594084f, 4.834950455437025f, 2.8761583089954956f, 19.052270926160006f, 15.24777552106931f, 29.503982821425833f, 28.0239095609042f, 29.835756997785094f, 6.974215220034302f, 13.340923653590902f, 7.523422855234715f, 17.73712036643994f, 18.72492152264347f, 24.00622366903189f, 21.28494911488049f, 7.69827865464105f, 12.690507682875648f, 15.785698313417537f, 0.1447434316088514f, 1.0649823512329382f, 12.261792531662229f, 3.33524901689928f, 21.71309018607915f, 7.225965433249898f, 2.993192602649729f, 5.452802349012758f, 6.9457628813142245f, 6.5206090415507765f, 15.622090921436925f, 13.932093334315208f, 9.29178212632239f, 19.25276273042024f, 6.373492259834692f, 27.196880301950472f, 28.89349964487713f, 21.867931367325728f, 13.01201606368995f, 15.34504026651143f, 17.432289181204784f, 1.5370423081749007f, 12.54049165447369f, 15.751935969592854f, 5.436751824755146f, 2.81360365374955f, 24.07965626116158f, 10.985518996301938f, 15.576290702969565f, 27.643510427756077f, 18.31531011309091f, 8.687423025904899f, 29.50563220659956f, 11.166801298024023f, 0.5716531442881378f, 20.559320169446085f, 3.0348562683947042f, 9.177670821187947f, 25.218350613565224f, 20.17715263934298f, 0.4716621664301457f, 13.54270377605947f, 12.320231267205209f, 14.575888320060034f, 6.2474068007339305f, 17.66235186462625f, 2.213679404257589f, 8.530780529411576f, 11.187063151409038f, 28.05811302145533f, 2.2964466108006087f, 22.64952342743696f, 5.770773839004716f, 17.146582239879926f, 11.753429110927433f, 13.896731467470222f, 22.60741517207155f, 11.851276804735885f, 3.6518844040100875f, 3.6531029916461986f, 2.4153215326088953f, 25.502126217145438f, 19.22974781493195f, 28.790056901874365f, 20.779576399639488f, 0.7400631796230317f, 19.77478991531755f, 23.31635803949396f, 21.70554839949389f, 14.938485612888524f, 10.727538531929156f, 13.71107141855355f, 23.961662510390394f, 8.068274814829577f, 15.789112344189004f, 14.326786261695656f, 28.640905408839924f, 24.13049930758013f, 27.961615806547155f, 25.080167207171822f, 8.90291006744023f, 6.948820834547174f, 14.663684203450902f, 7.782160240835196f, 12.829614958677857f, 20.374206460834465f, 27.557406816850055f, 17.577017410353022f, 24.5355976169745f, 2.8784193257599746f, 10.681716839105125f, 29.93244064120892f, 4.395031438686942f, 12.503041304246661f, 2.0051818635844842f, 2.58448069796698f, 26.86501056284191f, 29.659110861229273f, 19.44246233349408f, 3.8554501475203007f, 8.891475585980874f, 6.950989300400724f, 20.12196977849825f, 20.43297022493511f, 13.165375107347339f, 15.719843049419296f, 3.362107907835723f, 16.22679747343502f, 28.498161651684075f, 22.673319076830868f, 2.8846338381268732f, 15.495040844813204f, 21.46094452906384f, 7.717815526477821f, 26.846899499932935f, 13.828228923839157f, 21.096936293195274f, 12.12490168388222f, 29.853991126690776f, 23.484472132698677f, 17.203212021795913f, 4.342950686810733f, 13.235497784361648f, 0.8815472892817433f, 17.854925256204158f, 26.454525531102696f, 5.412734760237447f, 15.30514509683229f, 14.47374975844103f, 12.147440371004084f, 21.31380239082444f, 28.10009756955776f, 21.161776106341588f, 14.174975386285801f, 28.859322342480255f, 9.921825017018518f, 22.368382642858155f, 19.75455077322128f, 22.84826624833346f, 25.562196834189272f, 6.749966412675641f, 18.637470868500102f, 12.08171654111675f, 20.009156402026626f, 29.31702193936783f, 19.04492540247065f, 0.34817382237329f, 13.936464233005035f, 21.347294503460798f, 26.496628105560152f, 19.502550999232113f, 24.482097050792696f, 0.5141218907210998f, 28.296886954425393f, 21.883909009978364f, 18.193318557542334f, 27.15969090510142f, 26.54039181156207f, 3.013721419122252f, 24.468636488405615f, 23.01002222335158f, 5.986141400279795f, 22.327370775055996f, 17.586823310007755f, 5.744832714603162f, 24.12568187980187f, 4.136193843592172f, 18.369711193150856f, 13.031939524871754f, 7.610733325803549f, 16.9828386992738f, 14.01260637776116f, 6.149924838331157f, 29.003423622286192f, 2.1847610213393587f, 0.09111864246665768f, 14.562693878970936f, 25.11574491912604f, 19.75206190320358f, 22.6400876622412f, 14.550013599902703f, 20.24407064666962f, 10.046719117307441f, 8.00835792962951f, 15.087021245134029f, 0.8258344949231056f, 2.3942576974966645f, 22.618792209245914f, 5.210989138399996f, 22.50767177459249f}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // placeholder16
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // param21
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_three_symmetric_all_inputs_as_internal", get_test_model_three_symmetric_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({28.68102815667748f, 28.43482461178048f, 1.6965410318042606f, 2.546159854767649f, 25.064966343883487f, 22.079099672055698f, 20.091912043206626f, 9.244093727674326f, 18.178324970353874f, 18.204052009225137f, 17.43612051336009f, 4.751486107644167f, 12.920089208738059f, 11.80595460616114f, 21.690362437123976f, 29.84458688849228f, 28.481864192797307f, 16.325311422879626f, 13.345625661775607f, 8.047222249479843f, 1.0777298817857284f, 0.8233457127245702f, 13.946815862919363f, 9.553953835610322f, 11.400447657021349f, 26.75368373484862f, 15.772583074380849f, 16.815310830794967f, 7.083702213451862f, 0.7157423742234659f, 9.7542878628348f, 4.1009217895939996f, 15.306715375116035f, 29.96050704577656f, 20.234390920376104f, 5.455304904694332f, 26.807146097489653f, 23.902797642649187f, 22.03205075681933f, 27.19780949692683f, 22.88656451499213f, 23.692429123852897f, 10.613609335248105f, 29.429297192163798f, 28.857028136946774f, 4.835539599120566f, 22.620122149556163f, 21.454526947123604f, 13.84220093225933f, 15.91067148370335f, 14.70041765550574f, 27.74496216283711f, 15.025231878919646f, 24.945734693754368f, 10.617726146061477f, 26.485527557437592f, 26.991017662698773f, 13.83036494644913f, 17.03115211260733f, 27.609913175757864f, 21.71318861616055f, 14.598256645847552f, 6.654330329730326f, 9.74001731306694f, 20.987149142107306f, 4.9820905648237845f, 27.238214898782836f, 8.04412538699449f, 27.341335076041403f, 9.286893748483822f, 28.72085134668474f, 21.18617419102814f, 15.127464509499527f, 15.532432684456563f, 19.542431969003722f, 17.638341353834537f, 9.355329736530006f, 6.234554236137817f, 15.356749750658475f, 28.02463077401336f, 18.69795260177617f, 2.2612610722213624f, 24.611999841360507f, 21.778478624318943f, 27.229608628539626f, 5.742081999123525f, 22.343481728320626f, 1.7627668919596717f, 19.58729782303649f, 8.19299197011448f, 6.798495877342892f, 26.264735143447137f, 3.1879794793657465f, 15.670879960767898f, 25.61829021554616f, 7.344959339070507f, 6.314368160869394f, 26.4174527809884f, 12.687529451690882f, 21.50883296714926f, 0.9561921038023535f, 10.870707339097219f, 5.156429763771971f, 20.182963242406252f, 2.4870953221372663f, 28.63686496037243f, 0.7603414448070311f, 21.88270522325412f, 0.6343460916945198f, 7.670701621723278f, 24.400631622068275f, 4.713548660603247f, 5.512164277529285f, 20.744862780407722f, 11.566976440576816f, 1.2948298739249797f, 29.700046386084033f, 4.542603262696546f, 1.0880698273024203f, 10.32603016610384f, 18.457184499745726f, 22.27378869377339f, 3.3934470905423075f, 10.116413195899357f, 0.9243257288006568f, 13.45959787476882f, 22.979098097642343f, 22.198399911621014f, 27.060604750501103f, 22.669864610251928f, 25.873373289762835f, 21.160354201522967f, 14.18338536294938f, 6.7658271104366285f, 19.824854959710414f, 9.489177801847775f, 3.0614731514909463f, 13.434655842574534f, 26.24289124043902f, 3.826093938563636f, 17.54867094331822f, 11.78857650315502f, 15.444080902925313f, 4.314883919308318f, 28.791935594614824f, 7.772892697566165f, 18.182338171605082f, 12.592666369672408f, 0.5409965737477984f, 16.7385037151724f, 4.217081368840027f, 1.703429874695892f, 1.0066873874594084f, 4.834950455437025f, 2.8761583089954956f, 19.052270926160006f, 15.24777552106931f, 29.503982821425833f, 28.0239095609042f, 29.835756997785094f, 6.974215220034302f, 13.340923653590902f, 7.523422855234715f, 17.73712036643994f, 18.72492152264347f, 24.00622366903189f, 21.28494911488049f, 7.69827865464105f, 12.690507682875648f, 15.785698313417537f, 0.1447434316088514f, 1.0649823512329382f, 12.261792531662229f, 3.33524901689928f, 21.71309018607915f, 7.225965433249898f, 2.993192602649729f, 5.452802349012758f, 6.9457628813142245f, 6.5206090415507765f, 15.622090921436925f, 13.932093334315208f, 9.29178212632239f, 19.25276273042024f, 6.373492259834692f, 27.196880301950472f, 28.89349964487713f, 21.867931367325728f, 13.01201606368995f, 15.34504026651143f, 17.432289181204784f, 1.5370423081749007f, 12.54049165447369f, 15.751935969592854f, 5.436751824755146f, 2.81360365374955f, 24.07965626116158f, 10.985518996301938f, 15.576290702969565f, 27.643510427756077f, 18.31531011309091f, 8.687423025904899f, 29.50563220659956f, 11.166801298024023f, 0.5716531442881378f, 20.559320169446085f, 3.0348562683947042f, 9.177670821187947f, 25.218350613565224f, 20.17715263934298f, 0.4716621664301457f, 13.54270377605947f, 12.320231267205209f, 14.575888320060034f, 6.2474068007339305f, 17.66235186462625f, 2.213679404257589f, 8.530780529411576f, 11.187063151409038f, 28.05811302145533f, 2.2964466108006087f, 22.64952342743696f, 5.770773839004716f, 17.146582239879926f, 11.753429110927433f, 13.896731467470222f, 22.60741517207155f, 11.851276804735885f, 3.6518844040100875f, 3.6531029916461986f, 2.4153215326088953f, 25.502126217145438f, 19.22974781493195f, 28.790056901874365f, 20.779576399639488f, 0.7400631796230317f, 19.77478991531755f, 23.31635803949396f, 21.70554839949389f, 14.938485612888524f, 10.727538531929156f, 13.71107141855355f, 23.961662510390394f, 8.068274814829577f, 15.789112344189004f, 14.326786261695656f, 28.640905408839924f, 24.13049930758013f, 27.961615806547155f, 25.080167207171822f, 8.90291006744023f, 6.948820834547174f, 14.663684203450902f, 7.782160240835196f, 12.829614958677857f, 20.374206460834465f, 27.557406816850055f, 17.577017410353022f, 24.5355976169745f, 2.8784193257599746f, 10.681716839105125f, 29.93244064120892f, 4.395031438686942f, 12.503041304246661f, 2.0051818635844842f, 2.58448069796698f, 26.86501056284191f, 29.659110861229273f, 19.44246233349408f, 3.8554501475203007f, 8.891475585980874f, 6.950989300400724f, 20.12196977849825f, 20.43297022493511f, 13.165375107347339f, 15.719843049419296f, 3.362107907835723f, 16.22679747343502f, 28.498161651684075f, 22.673319076830868f, 2.8846338381268732f, 15.495040844813204f, 21.46094452906384f, 7.717815526477821f, 26.846899499932935f, 13.828228923839157f, 21.096936293195274f, 12.12490168388222f, 29.853991126690776f, 23.484472132698677f, 17.203212021795913f, 4.342950686810733f, 13.235497784361648f, 0.8815472892817433f, 17.854925256204158f, 26.454525531102696f, 5.412734760237447f, 15.30514509683229f, 14.47374975844103f, 12.147440371004084f, 21.31380239082444f, 28.10009756955776f, 21.161776106341588f, 14.174975386285801f, 28.859322342480255f, 9.921825017018518f, 22.368382642858155f, 19.75455077322128f, 22.84826624833346f, 25.562196834189272f, 6.749966412675641f, 18.637470868500102f, 12.08171654111675f, 20.009156402026626f, 29.31702193936783f, 19.04492540247065f, 0.34817382237329f, 13.936464233005035f, 21.347294503460798f, 26.496628105560152f, 19.502550999232113f, 24.482097050792696f, 0.5141218907210998f, 28.296886954425393f, 21.883909009978364f, 18.193318557542334f, 27.15969090510142f, 26.54039181156207f, 3.013721419122252f, 24.468636488405615f, 23.01002222335158f, 5.986141400279795f, 22.327370775055996f, 17.586823310007755f, 5.744832714603162f, 24.12568187980187f, 4.136193843592172f, 18.369711193150856f, 13.031939524871754f, 7.610733325803549f, 16.9828386992738f, 14.01260637776116f, 6.149924838331157f, 29.003423622286192f, 2.1847610213393587f, 0.09111864246665768f, 14.562693878970936f, 25.11574491912604f, 19.75206190320358f, 22.6400876622412f, 14.550013599902703f, 20.24407064666962f, 10.046719117307441f, 8.00835792962951f, 15.087021245134029f, 0.8258344949231056f, 2.3942576974966645f, 22.618792209245914f, 5.210989138399996f, 22.50767177459249f}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({23.01002222335158f, 23.01002222335158f, 5.986141400279795f, 22.327370775055996f, 17.586823310007755f, 5.744832714603162f, 24.12568187980187f, 24.12568187980187f, 23.01002222335158f, 23.01002222335158f, 5.986141400279795f, 22.327370775055996f, 17.586823310007755f, 5.744832714603162f, 24.12568187980187f, 24.12568187980187f, 4.136193843592172f, 4.136193843592172f, 18.369711193150856f, 13.031939524871754f, 7.610733325803549f, 16.9828386992738f, 14.01260637776116f, 14.01260637776116f, 6.149924838331157f, 6.149924838331157f, 29.003423622286192f, 2.1847610213393587f, 0.09111864246665768f, 14.562693878970936f, 25.11574491912604f, 25.11574491912604f, 19.75206190320358f, 19.75206190320358f, 22.6400876622412f, 14.550013599902703f, 20.24407064666962f, 10.046719117307441f, 8.00835792962951f, 8.00835792962951f, 15.087021245134029f, 15.087021245134029f, 0.8258344949231056f, 2.3942576974966645f, 22.618792209245914f, 5.210989138399996f, 22.50767177459249f, 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2.546159854767649f, 25.064966343883487f, 22.079099672055698f, 22.079099672055698f, 28.68102815667748f, 28.68102815667748f, 28.43482461178048f, 1.6965410318042606f, 2.546159854767649f, 25.064966343883487f, 22.079099672055698f, 22.079099672055698f, 28.68102815667748f, 28.68102815667748f, 28.43482461178048f, 1.6965410318042606f, 2.546159854767649f, 25.064966343883487f, 22.079099672055698f, 22.079099672055698f, 20.091912043206626f, 20.091912043206626f, 9.244093727674326f, 18.178324970353874f, 18.204052009225137f, 17.43612051336009f, 4.751486107644167f, 4.751486107644167f, 12.920089208738059f, 12.920089208738059f, 11.80595460616114f, 21.690362437123976f, 29.84458688849228f, 28.481864192797307f, 16.325311422879626f, 16.325311422879626f, 13.345625661775607f, 13.345625661775607f, 8.047222249479843f, 1.0777298817857284f, 0.8233457127245702f, 13.946815862919363f, 9.553953835610322f, 9.553953835610322f, 11.400447657021349f, 11.400447657021349f, 26.75368373484862f, 15.772583074380849f, 16.815310830794967f, 7.083702213451862f, 0.7157423742234659f, 0.7157423742234659f, 11.400447657021349f, 11.400447657021349f, 26.75368373484862f, 15.772583074380849f, 16.815310830794967f, 7.083702213451862f, 0.7157423742234659f, 0.7157423742234659f, 13.345625661775607f, 13.345625661775607f, 8.047222249479843f, 1.0777298817857284f, 0.8233457127245702f, 13.946815862919363f, 9.553953835610322f, 9.553953835610322f, 12.920089208738059f, 12.920089208738059f, 11.80595460616114f, 21.690362437123976f, 29.84458688849228f, 28.481864192797307f, 16.325311422879626f, 16.325311422879626f, 20.091912043206626f, 20.091912043206626f, 9.244093727674326f, 18.178324970353874f, 18.204052009225137f, 17.43612051336009f, 4.751486107644167f, 4.751486107644167f, 28.68102815667748f, 28.68102815667748f, 28.43482461178048f, 1.6965410318042606f, 2.546159854767649f, 25.064966343883487f, 22.079099672055698f, 22.079099672055698f, 9.7542878628348f, 9.7542878628348f, 4.1009217895939996f, 15.306715375116035f, 29.96050704577656f, 20.234390920376104f, 5.455304904694332f, 5.455304904694332f, 9.7542878628348f, 9.7542878628348f, 4.1009217895939996f, 15.306715375116035f, 29.96050704577656f, 20.234390920376104f, 5.455304904694332f, 5.455304904694332f, 26.807146097489653f, 26.807146097489653f, 23.902797642649187f, 22.03205075681933f, 27.19780949692683f, 22.88656451499213f, 23.692429123852897f, 23.692429123852897f, 10.613609335248105f, 10.613609335248105f, 29.429297192163798f, 28.857028136946774f, 4.835539599120566f, 22.620122149556163f, 21.454526947123604f, 21.454526947123604f, 13.84220093225933f, 13.84220093225933f, 15.91067148370335f, 14.70041765550574f, 27.74496216283711f, 15.025231878919646f, 24.945734693754368f, 24.945734693754368f, 10.617726146061477f, 10.617726146061477f, 26.485527557437592f, 26.991017662698773f, 13.83036494644913f, 17.03115211260733f, 27.609913175757864f, 27.609913175757864f, 10.617726146061477f, 10.617726146061477f, 26.485527557437592f, 26.991017662698773f, 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20.987149142107306f, 4.9820905648237845f, 4.9820905648237845f, 27.238214898782836f, 27.238214898782836f, 8.04412538699449f, 27.341335076041403f, 9.286893748483822f, 28.72085134668474f, 21.18617419102814f, 21.18617419102814f, 15.127464509499527f, 15.127464509499527f, 15.532432684456563f, 19.542431969003722f, 17.638341353834537f, 9.355329736530006f, 6.234554236137817f, 6.234554236137817f, 15.356749750658475f, 15.356749750658475f, 28.02463077401336f, 18.69795260177617f, 2.2612610722213624f, 24.611999841360507f, 21.778478624318943f, 21.778478624318943f, 27.229608628539626f, 27.229608628539626f, 5.742081999123525f, 22.343481728320626f, 1.7627668919596717f, 19.58729782303649f, 8.19299197011448f, 8.19299197011448f, 27.229608628539626f, 27.229608628539626f, 5.742081999123525f, 22.343481728320626f, 1.7627668919596717f, 19.58729782303649f, 8.19299197011448f, 8.19299197011448f, 15.356749750658475f, 15.356749750658475f, 28.02463077401336f, 18.69795260177617f, 2.2612610722213624f, 24.611999841360507f, 21.778478624318943f, 21.778478624318943f, 15.127464509499527f, 15.127464509499527f, 15.532432684456563f, 19.542431969003722f, 17.638341353834537f, 9.355329736530006f, 6.234554236137817f, 6.234554236137817f, 27.238214898782836f, 27.238214898782836f, 8.04412538699449f, 27.341335076041403f, 9.286893748483822f, 28.72085134668474f, 21.18617419102814f, 21.18617419102814f, 21.71318861616055f, 21.71318861616055f, 14.598256645847552f, 6.654330329730326f, 9.74001731306694f, 20.987149142107306f, 4.9820905648237845f, 4.9820905648237845f, 6.798495877342892f, 6.798495877342892f, 26.264735143447137f, 3.1879794793657465f, 15.670879960767898f, 25.61829021554616f, 7.344959339070507f, 7.344959339070507f, 6.798495877342892f, 6.798495877342892f, 26.264735143447137f, 3.1879794793657465f, 15.670879960767898f, 25.61829021554616f, 7.344959339070507f, 7.344959339070507f, 6.314368160869394f, 6.314368160869394f, 26.4174527809884f, 12.687529451690882f, 21.50883296714926f, 0.9561921038023535f, 10.870707339097219f, 10.870707339097219f, 5.156429763771971f, 5.156429763771971f, 20.182963242406252f, 2.4870953221372663f, 28.63686496037243f, 0.7603414448070311f, 21.88270522325412f, 21.88270522325412f, 0.6343460916945198f, 0.6343460916945198f, 7.670701621723278f, 24.400631622068275f, 4.713548660603247f, 5.512164277529285f, 20.744862780407722f, 20.744862780407722f, 11.566976440576816f, 11.566976440576816f, 1.2948298739249797f, 29.700046386084033f, 4.542603262696546f, 1.0880698273024203f, 10.32603016610384f, 10.32603016610384f, 11.566976440576816f, 11.566976440576816f, 1.2948298739249797f, 29.700046386084033f, 4.542603262696546f, 1.0880698273024203f, 10.32603016610384f, 10.32603016610384f, 0.6343460916945198f, 0.6343460916945198f, 7.670701621723278f, 24.400631622068275f, 4.713548660603247f, 5.512164277529285f, 20.744862780407722f, 20.744862780407722f, 5.156429763771971f, 5.156429763771971f, 20.182963242406252f, 2.4870953221372663f, 28.63686496037243f, 0.7603414448070311f, 21.88270522325412f, 21.88270522325412f, 6.314368160869394f, 6.314368160869394f, 26.4174527809884f, 12.687529451690882f, 21.50883296714926f, 0.9561921038023535f, 10.870707339097219f, 10.870707339097219f, 6.798495877342892f, 6.798495877342892f, 26.264735143447137f, 3.1879794793657465f, 15.670879960767898f, 25.61829021554616f, 7.344959339070507f, 7.344959339070507f, 6.798495877342892f, 6.798495877342892f, 26.264735143447137f, 3.1879794793657465f, 15.670879960767898f, 25.61829021554616f, 7.344959339070507f, 7.344959339070507f, 6.798495877342892f, 6.798495877342892f, 26.264735143447137f, 3.1879794793657465f, 15.670879960767898f, 25.61829021554616f, 7.344959339070507f, 7.344959339070507f, 6.314368160869394f, 6.314368160869394f, 26.4174527809884f, 12.687529451690882f, 21.50883296714926f, 0.9561921038023535f, 10.870707339097219f, 10.870707339097219f, 5.156429763771971f, 5.156429763771971f, 20.182963242406252f, 2.4870953221372663f, 28.63686496037243f, 0.7603414448070311f, 21.88270522325412f, 21.88270522325412f, 0.6343460916945198f, 0.6343460916945198f, 7.670701621723278f, 24.400631622068275f, 4.713548660603247f, 5.512164277529285f, 20.744862780407722f, 20.744862780407722f, 11.566976440576816f, 11.566976440576816f, 1.2948298739249797f, 29.700046386084033f, 4.542603262696546f, 1.0880698273024203f, 10.32603016610384f, 10.32603016610384f, 11.566976440576816f, 11.566976440576816f, 1.2948298739249797f, 29.700046386084033f, 4.542603262696546f, 1.0880698273024203f, 10.32603016610384f, 10.32603016610384f, 0.6343460916945198f, 0.6343460916945198f, 7.670701621723278f, 24.400631622068275f, 4.713548660603247f, 5.512164277529285f, 20.744862780407722f, 20.744862780407722f, 5.156429763771971f, 5.156429763771971f, 20.182963242406252f, 2.4870953221372663f, 28.63686496037243f, 0.7603414448070311f, 21.88270522325412f, 21.88270522325412f, 6.314368160869394f, 6.314368160869394f, 26.4174527809884f, 12.687529451690882f, 21.50883296714926f, 0.9561921038023535f, 10.870707339097219f, 10.870707339097219f, 6.798495877342892f, 6.798495877342892f, 26.264735143447137f, 3.1879794793657465f, 15.670879960767898f, 25.61829021554616f, 7.344959339070507f, 7.344959339070507f, 21.71318861616055f, 21.71318861616055f, 14.598256645847552f, 6.654330329730326f, 9.74001731306694f, 20.987149142107306f, 4.9820905648237845f, 4.9820905648237845f, 21.71318861616055f, 21.71318861616055f, 14.598256645847552f, 6.654330329730326f, 9.74001731306694f, 20.987149142107306f, 4.9820905648237845f, 4.9820905648237845f, 27.238214898782836f, 27.238214898782836f, 8.04412538699449f, 27.341335076041403f, 9.286893748483822f, 28.72085134668474f, 21.18617419102814f, 21.18617419102814f, 15.127464509499527f, 15.127464509499527f, 15.532432684456563f, 19.542431969003722f, 17.638341353834537f, 9.355329736530006f, 6.234554236137817f, 6.234554236137817f, 15.356749750658475f, 15.356749750658475f, 28.02463077401336f, 18.69795260177617f, 2.2612610722213624f, 24.611999841360507f, 21.778478624318943f, 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4.9820905648237845f}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_three_symmetric_all_tensors_as_inputs", get_test_model_three_symmetric_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({23.01002222335158f, 23.01002222335158f, 5.986141400279795f, 22.327370775055996f, 17.586823310007755f, 5.744832714603162f, 24.12568187980187f, 24.12568187980187f, 23.01002222335158f, 23.01002222335158f, 5.986141400279795f, 22.327370775055996f, 17.586823310007755f, 5.744832714603162f, 24.12568187980187f, 24.12568187980187f, 4.136193843592172f, 4.136193843592172f, 18.369711193150856f, 13.031939524871754f, 7.610733325803549f, 16.9828386992738f, 14.01260637776116f, 14.01260637776116f, 6.149924838331157f, 6.149924838331157f, 29.003423622286192f, 2.1847610213393587f, 0.09111864246665768f, 14.562693878970936f, 25.11574491912604f, 25.11574491912604f, 19.75206190320358f, 19.75206190320358f, 22.6400876622412f, 14.550013599902703f, 20.24407064666962f, 10.046719117307441f, 8.00835792962951f, 8.00835792962951f, 15.087021245134029f, 15.087021245134029f, 0.8258344949231056f, 2.3942576974966645f, 22.618792209245914f, 5.210989138399996f, 22.50767177459249f, 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4.9820905648237845f}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // in4_new
+ .channelQuant = {},
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1.5370423081749007f, 12.54049165447369f, 15.751935969592854f, 5.436751824755146f, 2.81360365374955f, 24.07965626116158f, 10.985518996301938f, 15.576290702969565f, 27.643510427756077f, 18.31531011309091f, 8.687423025904899f, 29.50563220659956f, 11.166801298024023f, 0.5716531442881378f, 20.559320169446085f, 3.0348562683947042f, 9.177670821187947f, 25.218350613565224f, 20.17715263934298f, 0.4716621664301457f, 13.54270377605947f, 12.320231267205209f, 14.575888320060034f, 6.2474068007339305f, 17.66235186462625f, 2.213679404257589f, 8.530780529411576f, 11.187063151409038f, 28.05811302145533f, 2.2964466108006087f, 22.64952342743696f, 5.770773839004716f, 17.146582239879926f, 11.753429110927433f, 13.896731467470222f, 22.60741517207155f, 11.851276804735885f, 3.6518844040100875f, 3.6531029916461986f, 2.4153215326088953f, 25.502126217145438f, 19.22974781493195f, 28.790056901874365f, 20.779576399639488f, 0.7400631796230317f, 19.77478991531755f, 23.31635803949396f, 21.70554839949389f, 14.938485612888524f, 10.727538531929156f, 13.71107141855355f, 23.961662510390394f, 8.068274814829577f, 15.789112344189004f, 14.326786261695656f, 28.640905408839924f, 24.13049930758013f, 27.961615806547155f, 25.080167207171822f, 8.90291006744023f, 6.948820834547174f, 14.663684203450902f, 7.782160240835196f, 12.829614958677857f, 20.374206460834465f, 27.557406816850055f, 17.577017410353022f, 24.5355976169745f, 2.8784193257599746f, 10.681716839105125f, 29.93244064120892f, 4.395031438686942f, 12.503041304246661f, 2.0051818635844842f, 2.58448069796698f, 26.86501056284191f, 29.659110861229273f, 19.44246233349408f, 3.8554501475203007f, 8.891475585980874f, 6.950989300400724f, 20.12196977849825f, 20.43297022493511f, 13.165375107347339f, 15.719843049419296f, 3.362107907835723f, 16.22679747343502f, 28.498161651684075f, 22.673319076830868f, 2.8846338381268732f, 15.495040844813204f, 21.46094452906384f, 7.717815526477821f, 26.846899499932935f, 13.828228923839157f, 21.096936293195274f, 12.12490168388222f, 29.853991126690776f, 23.484472132698677f, 17.203212021795913f, 4.342950686810733f, 13.235497784361648f, 0.8815472892817433f, 17.854925256204158f, 26.454525531102696f, 5.412734760237447f, 15.30514509683229f, 14.47374975844103f, 12.147440371004084f, 21.31380239082444f, 28.10009756955776f, 21.161776106341588f, 14.174975386285801f, 28.859322342480255f, 9.921825017018518f, 22.368382642858155f, 19.75455077322128f, 22.84826624833346f, 25.562196834189272f, 6.749966412675641f, 18.637470868500102f, 12.08171654111675f, 20.009156402026626f, 29.31702193936783f, 19.04492540247065f, 0.34817382237329f, 13.936464233005035f, 21.347294503460798f, 26.496628105560152f, 19.502550999232113f, 24.482097050792696f, 0.5141218907210998f, 28.296886954425393f, 21.883909009978364f, 18.193318557542334f, 27.15969090510142f, 26.54039181156207f, 3.013721419122252f, 24.468636488405615f, 23.01002222335158f, 5.986141400279795f, 22.327370775055996f, 17.586823310007755f, 5.744832714603162f, 24.12568187980187f, 4.136193843592172f, 18.369711193150856f, 13.031939524871754f, 7.610733325803549f, 16.9828386992738f, 14.01260637776116f, 6.149924838331157f, 29.003423622286192f, 2.1847610213393587f, 0.09111864246665768f, 14.562693878970936f, 25.11574491912604f, 19.75206190320358f, 22.6400876622412f, 14.550013599902703f, 20.24407064666962f, 10.046719117307441f, 8.00835792962951f, 15.087021245134029f, 0.8258344949231056f, 2.3942576974966645f, 22.618792209245914f, 5.210989138399996f, 22.50767177459249f}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // placeholder17
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // param22
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_three_symmetric_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_three_symmetric_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_float16() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({28.681028366088867f, 28.434823989868164f, 1.6965410709381104f, 2.5461597442626953f, 25.064966201782227f, 22.079099655151367f, 20.09191131591797f, 9.244093894958496f, 18.178325653076172f, 18.204051971435547f, 17.436120986938477f, 4.751486301422119f, 12.920088768005371f, 11.805954933166504f, 21.69036293029785f, 29.844587326049805f, 28.48186492919922f, 16.3253116607666f, 13.345625877380371f, 8.047222137451172f, 1.0777299404144287f, 0.8233457207679749f, 13.946815490722656f, 9.553954124450684f, 11.400447845458984f, 26.75368309020996f, 15.7725830078125f, 16.815311431884766f, 7.083702087402344f, 0.7157423496246338f, 9.754287719726562f, 4.100921630859375f, 15.30671501159668f, 29.960506439208984f, 20.234390258789062f, 5.455305099487305f, 26.807146072387695f, 23.90279769897461f, 22.03205108642578f, 27.19780921936035f, 22.886564254760742f, 23.692428588867188f, 10.613609313964844f, 29.429296493530273f, 28.85702896118164f, 4.835539817810059f, 22.6201229095459f, 21.454526901245117f, 13.842201232910156f, 15.91067123413086f, 14.700417518615723f, 27.744962692260742f, 15.025232315063477f, 24.94573402404785f, 10.61772632598877f, 26.48552703857422f, 26.991018295288086f, 13.830365180969238f, 17.031152725219727f, 27.609912872314453f, 21.71318817138672f, 14.598257064819336f, 6.654330253601074f, 9.74001693725586f, 20.98714828491211f, 4.982090473175049f, 27.23821449279785f, 8.0441255569458f, 27.34133529663086f, 9.286893844604492f, 28.72085189819336f, 21.186174392700195f, 15.127464294433594f, 15.532432556152344f, 19.54243278503418f, 17.638341903686523f, 9.355329513549805f, 6.234554290771484f, 15.356749534606934f, 28.02463150024414f, 18.697952270507812f, 2.261260986328125f, 24.61199951171875f, 21.778478622436523f, 27.2296085357666f, 5.742082118988037f, 22.343481063842773f, 1.7627668380737305f, 19.587297439575195f, 8.192992210388184f, 6.798495769500732f, 26.264734268188477f, 3.1879794597625732f, 15.670880317687988f, 25.618289947509766f, 7.344959259033203f, 6.31436824798584f, 26.417451858520508f, 12.687529563903809f, 21.508832931518555f, 0.9561920762062073f, 10.870707511901855f, 5.156429767608643f, 20.18296241760254f, 2.487095355987549f, 28.636865615844727f, 0.760341465473175f, 21.882705688476562f, 0.634346067905426f, 7.670701503753662f, 24.400630950927734f, 4.71354866027832f, 5.512164115905762f, 20.744863510131836f, 11.566976547241211f, 1.2948298454284668f, 29.70004653930664f, 4.542603492736816f, 1.0880697965621948f, 10.326029777526855f, 18.457183837890625f, 22.273788452148438f, 3.393447160720825f, 10.116413116455078f, 0.924325704574585f, 13.45959758758545f, 22.979097366333008f, 22.198400497436523f, 27.060604095458984f, 22.669864654541016f, 25.87337303161621f, 21.160354614257812f, 14.183384895324707f, 6.765827178955078f, 19.82485580444336f, 9.489177703857422f, 3.0614731311798096f, 13.434656143188477f, 26.242891311645508f, 3.826093912124634f, 17.54867172241211f, 11.788576126098633f, 15.44408130645752f, 4.314883708953857f, 28.791934967041016f, 7.772892475128174f, 18.18233871459961f, 12.592666625976562f, 0.5409965515136719f, 16.73850440979004f, 4.217081546783447f, 1.7034298181533813f, 1.0066874027252197f, 4.8349504470825195f, 2.8761582374572754f, 19.052270889282227f, 15.247775077819824f, 29.503982543945312f, 28.023908615112305f, 29.835756301879883f, 6.974215030670166f, 13.340923309326172f, 7.523422718048096f, 17.737119674682617f, 18.72492218017578f, 24.006223678588867f, 21.284948348999023f, 7.698278427124023f, 12.690507888793945f, 15.785697937011719f, 0.1447434276342392f, 1.064982295036316f, 12.261792182922363f, 3.3352489471435547f, 21.713090896606445f, 7.22596549987793f, 2.993192672729492f, 5.4528021812438965f, 6.945763111114502f, 6.520608901977539f, 15.622091293334961f, 13.932093620300293f, 9.29178237915039f, 19.252761840820312f, 6.373492240905762f, 27.196880340576172f, 28.89349937438965f, 21.867931365966797f, 13.012016296386719f, 15.345040321350098f, 17.432289123535156f, 1.537042260169983f, 12.540492057800293f, 15.751935958862305f, 5.436751842498779f, 2.813603639602661f, 24.07965660095215f, 10.985519409179688f, 15.57629108428955f, 27.643510818481445f, 18.315309524536133f, 8.687422752380371f, 29.505632400512695f, 11.166801452636719f, 0.5716531276702881f, 20.5593204498291f, 3.0348563194274902f, 9.1776704788208f, 25.218351364135742f, 20.177152633666992f, 0.47166216373443604f, 13.542703628540039f, 12.320231437683105f, 14.575888633728027f, 6.247406959533691f, 17.662351608276367f, 2.213679313659668f, 8.530780792236328f, 11.187063217163086f, 28.05811309814453f, 2.2964465618133545f, 22.64952278137207f, 5.770773887634277f, 17.146581649780273f, 11.753429412841797f, 13.89673137664795f, 22.60741424560547f, 11.851276397705078f, 3.6518843173980713f, 3.6531028747558594f, 2.4153215885162354f, 25.502126693725586f, 19.229747772216797f, 28.790056228637695f, 20.779577255249023f, 0.7400631904602051f, 19.774789810180664f, 23.31635856628418f, 21.705549240112305f, 14.938485145568848f, 10.727538108825684f, 13.711071014404297f, 23.96166229248047f, 8.06827449798584f, 15.789112091064453f, 14.326786041259766f, 28.640905380249023f, 24.1304988861084f, 27.96161651611328f, 25.080167770385742f, 8.902910232543945f, 6.948821067810059f, 14.663683891296387f, 7.78216028213501f, 12.829614639282227f, 20.37420654296875f, 27.55740737915039f, 17.577016830444336f, 24.53559684753418f, 2.8784193992614746f, 10.681716918945312f, 29.93243980407715f, 4.395031452178955f, 12.50304126739502f, 2.0051817893981934f, 2.5844807624816895f, 26.86501121520996f, 29.65911102294922f, 19.442462921142578f, 3.85545015335083f, 8.891475677490234f, 6.950989246368408f, 20.12196922302246f, 20.43297004699707f, 13.165374755859375f, 15.719842910766602f, 3.362107992172241f, 16.226797103881836f, 28.49816131591797f, 22.67331886291504f, 2.884633779525757f, 15.495040893554688f, 21.46094512939453f, 7.717815399169922f, 26.846899032592773f, 13.828228950500488f, 21.09693717956543f, 12.12490177154541f, 29.85399055480957f, 23.484472274780273f, 17.20321273803711f, 4.342950820922852f, 13.23549747467041f, 0.8815472722053528f, 17.85492515563965f, 26.454524993896484f, 5.4127349853515625f, 15.305145263671875f, 14.473750114440918f, 12.147439956665039f, 21.31380271911621f, 28.10009765625f, 21.161775588989258f, 14.174975395202637f, 28.85932159423828f, 9.921825408935547f, 22.368383407592773f, 19.75455093383789f, 22.8482666015625f, 25.562196731567383f, 6.749966621398926f, 18.637470245361328f, 12.081716537475586f, 20.009157180786133f, 29.3170223236084f, 19.044925689697266f, 0.3481738269329071f, 13.936464309692383f, 21.347293853759766f, 26.496627807617188f, 19.50255012512207f, 24.482097625732422f, 0.5141218900680542f, 28.296886444091797f, 21.883909225463867f, 18.19331932067871f, 27.159690856933594f, 26.54039192199707f, 3.013721466064453f, 24.46863555908203f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 4.136193752288818f, 18.36971092224121f, 13.031939506530762f, 7.610733509063721f, 16.982839584350586f, 14.012606620788574f, 6.1499247550964355f, 29.0034236907959f, 2.1847610473632812f, 0.09111864119768143f, 14.56269359588623f, 25.115745544433594f, 19.75206184387207f, 22.640087127685547f, 14.550013542175293f, 20.244070053100586f, 10.046719551086426f, 8.008358001708984f, 15.087020874023438f, 0.8258345127105713f, 2.3942577838897705f, 22.618791580200195f, 5.210988998413086f, 22.507671356201172f}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({23.01002311706543f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 24.125682830810547f, 23.01002311706543f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 24.125682830810547f, 4.136193752288818f, 4.136193752288818f, 18.36971092224121f, 13.031939506530762f, 7.610733509063721f, 16.982839584350586f, 14.012606620788574f, 14.012606620788574f, 6.1499247550964355f, 6.1499247550964355f, 29.0034236907959f, 2.1847610473632812f, 0.09111864119768143f, 14.56269359588623f, 25.115745544433594f, 25.115745544433594f, 19.75206184387207f, 19.75206184387207f, 22.640087127685547f, 14.550013542175293f, 20.244070053100586f, 10.046719551086426f, 8.008358001708984f, 8.008358001708984f, 15.087020874023438f, 15.087020874023438f, 0.8258345127105713f, 2.3942577838897705f, 22.618791580200195f, 5.210988998413086f, 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20.98714828491211f, 4.982090473175049f, 4.982090473175049f}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_float16 = TestModelManager::get().add("mirror_pad_three_symmetric_float16", get_test_model_three_symmetric_float16());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_float16_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({23.01002311706543f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 24.125682830810547f, 23.01002311706543f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 24.125682830810547f, 4.136193752288818f, 4.136193752288818f, 18.36971092224121f, 13.031939506530762f, 7.610733509063721f, 16.982839584350586f, 14.012606620788574f, 14.012606620788574f, 6.1499247550964355f, 6.1499247550964355f, 29.0034236907959f, 2.1847610473632812f, 0.09111864119768143f, 14.56269359588623f, 25.115745544433594f, 25.115745544433594f, 19.75206184387207f, 19.75206184387207f, 22.640087127685547f, 14.550013542175293f, 20.244070053100586f, 10.046719551086426f, 8.008358001708984f, 8.008358001708984f, 15.087020874023438f, 15.087020874023438f, 0.8258345127105713f, 2.3942577838897705f, 22.618791580200195f, 5.210988998413086f, 22.507671356201172f, 22.507671356201172f, 15.087020874023438f, 15.087020874023438f, 0.8258345127105713f, 2.3942577838897705f, 22.618791580200195f, 5.210988998413086f, 22.507671356201172f, 22.507671356201172f, 19.75206184387207f, 19.75206184387207f, 22.640087127685547f, 14.550013542175293f, 20.244070053100586f, 10.046719551086426f, 8.008358001708984f, 8.008358001708984f, 6.1499247550964355f, 6.1499247550964355f, 29.0034236907959f, 2.1847610473632812f, 0.09111864119768143f, 14.56269359588623f, 25.115745544433594f, 25.115745544433594f, 4.136193752288818f, 4.136193752288818f, 18.36971092224121f, 13.031939506530762f, 7.610733509063721f, 16.982839584350586f, 14.012606620788574f, 14.012606620788574f, 23.01002311706543f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 24.125682830810547f, 21.31380271911621f, 21.31380271911621f, 28.10009765625f, 21.161775588989258f, 14.174975395202637f, 28.85932159423828f, 9.921825408935547f, 9.921825408935547f, 21.31380271911621f, 21.31380271911621f, 28.10009765625f, 21.161775588989258f, 14.174975395202637f, 28.85932159423828f, 9.921825408935547f, 9.921825408935547f, 22.368383407592773f, 22.368383407592773f, 19.75455093383789f, 22.8482666015625f, 25.562196731567383f, 6.749966621398926f, 18.637470245361328f, 18.637470245361328f, 12.081716537475586f, 12.081716537475586f, 20.009157180786133f, 29.3170223236084f, 19.044925689697266f, 0.3481738269329071f, 13.936464309692383f, 13.936464309692383f, 21.347293853759766f, 21.347293853759766f, 26.496627807617188f, 19.50255012512207f, 24.482097625732422f, 0.5141218900680542f, 28.296886444091797f, 28.296886444091797f, 21.883909225463867f, 21.883909225463867f, 18.19331932067871f, 27.159690856933594f, 26.54039192199707f, 3.013721466064453f, 24.46863555908203f, 24.46863555908203f, 21.883909225463867f, 21.883909225463867f, 18.19331932067871f, 27.159690856933594f, 26.54039192199707f, 3.013721466064453f, 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12.687529563903809f, 21.508832931518555f, 0.9561920762062073f, 10.870707511901855f, 10.870707511901855f, 5.156429767608643f, 5.156429767608643f, 20.18296241760254f, 2.487095355987549f, 28.636865615844727f, 0.760341465473175f, 21.882705688476562f, 21.882705688476562f, 0.634346067905426f, 0.634346067905426f, 7.670701503753662f, 24.400630950927734f, 4.71354866027832f, 5.512164115905762f, 20.744863510131836f, 20.744863510131836f, 11.566976547241211f, 11.566976547241211f, 1.2948298454284668f, 29.70004653930664f, 4.542603492736816f, 1.0880697965621948f, 10.326029777526855f, 10.326029777526855f, 11.566976547241211f, 11.566976547241211f, 1.2948298454284668f, 29.70004653930664f, 4.542603492736816f, 1.0880697965621948f, 10.326029777526855f, 10.326029777526855f, 0.634346067905426f, 0.634346067905426f, 7.670701503753662f, 24.400630950927734f, 4.71354866027832f, 5.512164115905762f, 20.744863510131836f, 20.744863510131836f, 5.156429767608643f, 5.156429767608643f, 20.18296241760254f, 2.487095355987549f, 28.636865615844727f, 0.760341465473175f, 21.882705688476562f, 21.882705688476562f, 6.31436824798584f, 6.31436824798584f, 26.417451858520508f, 12.687529563903809f, 21.508832931518555f, 0.9561920762062073f, 10.870707511901855f, 10.870707511901855f, 6.798495769500732f, 6.798495769500732f, 26.264734268188477f, 3.1879794597625732f, 15.670880317687988f, 25.618289947509766f, 7.344959259033203f, 7.344959259033203f, 6.798495769500732f, 6.798495769500732f, 26.264734268188477f, 3.1879794597625732f, 15.670880317687988f, 25.618289947509766f, 7.344959259033203f, 7.344959259033203f, 6.798495769500732f, 6.798495769500732f, 26.264734268188477f, 3.1879794597625732f, 15.670880317687988f, 25.618289947509766f, 7.344959259033203f, 7.344959259033203f, 6.31436824798584f, 6.31436824798584f, 26.417451858520508f, 12.687529563903809f, 21.508832931518555f, 0.9561920762062073f, 10.870707511901855f, 10.870707511901855f, 5.156429767608643f, 5.156429767608643f, 20.18296241760254f, 2.487095355987549f, 28.636865615844727f, 0.760341465473175f, 21.882705688476562f, 21.882705688476562f, 0.634346067905426f, 0.634346067905426f, 7.670701503753662f, 24.400630950927734f, 4.71354866027832f, 5.512164115905762f, 20.744863510131836f, 20.744863510131836f, 11.566976547241211f, 11.566976547241211f, 1.2948298454284668f, 29.70004653930664f, 4.542603492736816f, 1.0880697965621948f, 10.326029777526855f, 10.326029777526855f, 11.566976547241211f, 11.566976547241211f, 1.2948298454284668f, 29.70004653930664f, 4.542603492736816f, 1.0880697965621948f, 10.326029777526855f, 10.326029777526855f, 0.634346067905426f, 0.634346067905426f, 7.670701503753662f, 24.400630950927734f, 4.71354866027832f, 5.512164115905762f, 20.744863510131836f, 20.744863510131836f, 5.156429767608643f, 5.156429767608643f, 20.18296241760254f, 2.487095355987549f, 28.636865615844727f, 0.760341465473175f, 21.882705688476562f, 21.882705688476562f, 6.31436824798584f, 6.31436824798584f, 26.417451858520508f, 12.687529563903809f, 21.508832931518555f, 0.9561920762062073f, 10.870707511901855f, 10.870707511901855f, 6.798495769500732f, 6.798495769500732f, 26.264734268188477f, 3.1879794597625732f, 15.670880317687988f, 25.618289947509766f, 7.344959259033203f, 7.344959259033203f, 21.71318817138672f, 21.71318817138672f, 14.598257064819336f, 6.654330253601074f, 9.74001693725586f, 20.98714828491211f, 4.982090473175049f, 4.982090473175049f, 21.71318817138672f, 21.71318817138672f, 14.598257064819336f, 6.654330253601074f, 9.74001693725586f, 20.98714828491211f, 4.982090473175049f, 4.982090473175049f, 27.23821449279785f, 27.23821449279785f, 8.0441255569458f, 27.34133529663086f, 9.286893844604492f, 28.72085189819336f, 21.186174392700195f, 21.186174392700195f, 15.127464294433594f, 15.127464294433594f, 15.532432556152344f, 19.54243278503418f, 17.638341903686523f, 9.355329513549805f, 6.234554290771484f, 6.234554290771484f, 15.356749534606934f, 15.356749534606934f, 28.02463150024414f, 18.697952270507812f, 2.261260986328125f, 24.61199951171875f, 21.778478622436523f, 21.778478622436523f, 27.2296085357666f, 27.2296085357666f, 5.742082118988037f, 22.343481063842773f, 1.7627668380737305f, 19.587297439575195f, 8.192992210388184f, 8.192992210388184f, 27.2296085357666f, 27.2296085357666f, 5.742082118988037f, 22.343481063842773f, 1.7627668380737305f, 19.587297439575195f, 8.192992210388184f, 8.192992210388184f, 15.356749534606934f, 15.356749534606934f, 28.02463150024414f, 18.697952270507812f, 2.261260986328125f, 24.61199951171875f, 21.778478622436523f, 21.778478622436523f, 15.127464294433594f, 15.127464294433594f, 15.532432556152344f, 19.54243278503418f, 17.638341903686523f, 9.355329513549805f, 6.234554290771484f, 6.234554290771484f, 27.23821449279785f, 27.23821449279785f, 8.0441255569458f, 27.34133529663086f, 9.286893844604492f, 28.72085189819336f, 21.186174392700195f, 21.186174392700195f, 21.71318817138672f, 21.71318817138672f, 14.598257064819336f, 6.654330253601074f, 9.74001693725586f, 20.98714828491211f, 4.982090473175049f, 4.982090473175049f}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // in4_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({28.681028366088867f, 28.434823989868164f, 1.6965410709381104f, 2.5461597442626953f, 25.064966201782227f, 22.079099655151367f, 20.09191131591797f, 9.244093894958496f, 18.178325653076172f, 18.204051971435547f, 17.436120986938477f, 4.751486301422119f, 12.920088768005371f, 11.805954933166504f, 21.69036293029785f, 29.844587326049805f, 28.48186492919922f, 16.3253116607666f, 13.345625877380371f, 8.047222137451172f, 1.0777299404144287f, 0.8233457207679749f, 13.946815490722656f, 9.553954124450684f, 11.400447845458984f, 26.75368309020996f, 15.7725830078125f, 16.815311431884766f, 7.083702087402344f, 0.7157423496246338f, 9.754287719726562f, 4.100921630859375f, 15.30671501159668f, 29.960506439208984f, 20.234390258789062f, 5.455305099487305f, 26.807146072387695f, 23.90279769897461f, 22.03205108642578f, 27.19780921936035f, 22.886564254760742f, 23.692428588867188f, 10.613609313964844f, 29.429296493530273f, 28.85702896118164f, 4.835539817810059f, 22.6201229095459f, 21.454526901245117f, 13.842201232910156f, 15.91067123413086f, 14.700417518615723f, 27.744962692260742f, 15.025232315063477f, 24.94573402404785f, 10.61772632598877f, 26.48552703857422f, 26.991018295288086f, 13.830365180969238f, 17.031152725219727f, 27.609912872314453f, 21.71318817138672f, 14.598257064819336f, 6.654330253601074f, 9.74001693725586f, 20.98714828491211f, 4.982090473175049f, 27.23821449279785f, 8.0441255569458f, 27.34133529663086f, 9.286893844604492f, 28.72085189819336f, 21.186174392700195f, 15.127464294433594f, 15.532432556152344f, 19.54243278503418f, 17.638341903686523f, 9.355329513549805f, 6.234554290771484f, 15.356749534606934f, 28.02463150024414f, 18.697952270507812f, 2.261260986328125f, 24.61199951171875f, 21.778478622436523f, 27.2296085357666f, 5.742082118988037f, 22.343481063842773f, 1.7627668380737305f, 19.587297439575195f, 8.192992210388184f, 6.798495769500732f, 26.264734268188477f, 3.1879794597625732f, 15.670880317687988f, 25.618289947509766f, 7.344959259033203f, 6.31436824798584f, 26.417451858520508f, 12.687529563903809f, 21.508832931518555f, 0.9561920762062073f, 10.870707511901855f, 5.156429767608643f, 20.18296241760254f, 2.487095355987549f, 28.636865615844727f, 0.760341465473175f, 21.882705688476562f, 0.634346067905426f, 7.670701503753662f, 24.400630950927734f, 4.71354866027832f, 5.512164115905762f, 20.744863510131836f, 11.566976547241211f, 1.2948298454284668f, 29.70004653930664f, 4.542603492736816f, 1.0880697965621948f, 10.326029777526855f, 18.457183837890625f, 22.273788452148438f, 3.393447160720825f, 10.116413116455078f, 0.924325704574585f, 13.45959758758545f, 22.979097366333008f, 22.198400497436523f, 27.060604095458984f, 22.669864654541016f, 25.87337303161621f, 21.160354614257812f, 14.183384895324707f, 6.765827178955078f, 19.82485580444336f, 9.489177703857422f, 3.0614731311798096f, 13.434656143188477f, 26.242891311645508f, 3.826093912124634f, 17.54867172241211f, 11.788576126098633f, 15.44408130645752f, 4.314883708953857f, 28.791934967041016f, 7.772892475128174f, 18.18233871459961f, 12.592666625976562f, 0.5409965515136719f, 16.73850440979004f, 4.217081546783447f, 1.7034298181533813f, 1.0066874027252197f, 4.8349504470825195f, 2.8761582374572754f, 19.052270889282227f, 15.247775077819824f, 29.503982543945312f, 28.023908615112305f, 29.835756301879883f, 6.974215030670166f, 13.340923309326172f, 7.523422718048096f, 17.737119674682617f, 18.72492218017578f, 24.006223678588867f, 21.284948348999023f, 7.698278427124023f, 12.690507888793945f, 15.785697937011719f, 0.1447434276342392f, 1.064982295036316f, 12.261792182922363f, 3.3352489471435547f, 21.713090896606445f, 7.22596549987793f, 2.993192672729492f, 5.4528021812438965f, 6.945763111114502f, 6.520608901977539f, 15.622091293334961f, 13.932093620300293f, 9.29178237915039f, 19.252761840820312f, 6.373492240905762f, 27.196880340576172f, 28.89349937438965f, 21.867931365966797f, 13.012016296386719f, 15.345040321350098f, 17.432289123535156f, 1.537042260169983f, 12.540492057800293f, 15.751935958862305f, 5.436751842498779f, 2.813603639602661f, 24.07965660095215f, 10.985519409179688f, 15.57629108428955f, 27.643510818481445f, 18.315309524536133f, 8.687422752380371f, 29.505632400512695f, 11.166801452636719f, 0.5716531276702881f, 20.5593204498291f, 3.0348563194274902f, 9.1776704788208f, 25.218351364135742f, 20.177152633666992f, 0.47166216373443604f, 13.542703628540039f, 12.320231437683105f, 14.575888633728027f, 6.247406959533691f, 17.662351608276367f, 2.213679313659668f, 8.530780792236328f, 11.187063217163086f, 28.05811309814453f, 2.2964465618133545f, 22.64952278137207f, 5.770773887634277f, 17.146581649780273f, 11.753429412841797f, 13.89673137664795f, 22.60741424560547f, 11.851276397705078f, 3.6518843173980713f, 3.6531028747558594f, 2.4153215885162354f, 25.502126693725586f, 19.229747772216797f, 28.790056228637695f, 20.779577255249023f, 0.7400631904602051f, 19.774789810180664f, 23.31635856628418f, 21.705549240112305f, 14.938485145568848f, 10.727538108825684f, 13.711071014404297f, 23.96166229248047f, 8.06827449798584f, 15.789112091064453f, 14.326786041259766f, 28.640905380249023f, 24.1304988861084f, 27.96161651611328f, 25.080167770385742f, 8.902910232543945f, 6.948821067810059f, 14.663683891296387f, 7.78216028213501f, 12.829614639282227f, 20.37420654296875f, 27.55740737915039f, 17.577016830444336f, 24.53559684753418f, 2.8784193992614746f, 10.681716918945312f, 29.93243980407715f, 4.395031452178955f, 12.50304126739502f, 2.0051817893981934f, 2.5844807624816895f, 26.86501121520996f, 29.65911102294922f, 19.442462921142578f, 3.85545015335083f, 8.891475677490234f, 6.950989246368408f, 20.12196922302246f, 20.43297004699707f, 13.165374755859375f, 15.719842910766602f, 3.362107992172241f, 16.226797103881836f, 28.49816131591797f, 22.67331886291504f, 2.884633779525757f, 15.495040893554688f, 21.46094512939453f, 7.717815399169922f, 26.846899032592773f, 13.828228950500488f, 21.09693717956543f, 12.12490177154541f, 29.85399055480957f, 23.484472274780273f, 17.20321273803711f, 4.342950820922852f, 13.23549747467041f, 0.8815472722053528f, 17.85492515563965f, 26.454524993896484f, 5.4127349853515625f, 15.305145263671875f, 14.473750114440918f, 12.147439956665039f, 21.31380271911621f, 28.10009765625f, 21.161775588989258f, 14.174975395202637f, 28.85932159423828f, 9.921825408935547f, 22.368383407592773f, 19.75455093383789f, 22.8482666015625f, 25.562196731567383f, 6.749966621398926f, 18.637470245361328f, 12.081716537475586f, 20.009157180786133f, 29.3170223236084f, 19.044925689697266f, 0.3481738269329071f, 13.936464309692383f, 21.347293853759766f, 26.496627807617188f, 19.50255012512207f, 24.482097625732422f, 0.5141218900680542f, 28.296886444091797f, 21.883909225463867f, 18.19331932067871f, 27.159690856933594f, 26.54039192199707f, 3.013721466064453f, 24.46863555908203f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 4.136193752288818f, 18.36971092224121f, 13.031939506530762f, 7.610733509063721f, 16.982839584350586f, 14.012606620788574f, 6.1499247550964355f, 29.0034236907959f, 2.1847610473632812f, 0.09111864119768143f, 14.56269359588623f, 25.115745544433594f, 19.75206184387207f, 22.640087127685547f, 14.550013542175293f, 20.244070053100586f, 10.046719551086426f, 8.008358001708984f, 15.087020874023438f, 0.8258345127105713f, 2.3942577838897705f, 22.618791580200195f, 5.210988998413086f, 22.507671356201172f}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // placeholder18
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // param23
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_float16_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_three_symmetric_float16_all_inputs_as_internal", get_test_model_three_symmetric_float16_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_float16_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({28.681028366088867f, 28.434823989868164f, 1.6965410709381104f, 2.5461597442626953f, 25.064966201782227f, 22.079099655151367f, 20.09191131591797f, 9.244093894958496f, 18.178325653076172f, 18.204051971435547f, 17.436120986938477f, 4.751486301422119f, 12.920088768005371f, 11.805954933166504f, 21.69036293029785f, 29.844587326049805f, 28.48186492919922f, 16.3253116607666f, 13.345625877380371f, 8.047222137451172f, 1.0777299404144287f, 0.8233457207679749f, 13.946815490722656f, 9.553954124450684f, 11.400447845458984f, 26.75368309020996f, 15.7725830078125f, 16.815311431884766f, 7.083702087402344f, 0.7157423496246338f, 9.754287719726562f, 4.100921630859375f, 15.30671501159668f, 29.960506439208984f, 20.234390258789062f, 5.455305099487305f, 26.807146072387695f, 23.90279769897461f, 22.03205108642578f, 27.19780921936035f, 22.886564254760742f, 23.692428588867188f, 10.613609313964844f, 29.429296493530273f, 28.85702896118164f, 4.835539817810059f, 22.6201229095459f, 21.454526901245117f, 13.842201232910156f, 15.91067123413086f, 14.700417518615723f, 27.744962692260742f, 15.025232315063477f, 24.94573402404785f, 10.61772632598877f, 26.48552703857422f, 26.991018295288086f, 13.830365180969238f, 17.031152725219727f, 27.609912872314453f, 21.71318817138672f, 14.598257064819336f, 6.654330253601074f, 9.74001693725586f, 20.98714828491211f, 4.982090473175049f, 27.23821449279785f, 8.0441255569458f, 27.34133529663086f, 9.286893844604492f, 28.72085189819336f, 21.186174392700195f, 15.127464294433594f, 15.532432556152344f, 19.54243278503418f, 17.638341903686523f, 9.355329513549805f, 6.234554290771484f, 15.356749534606934f, 28.02463150024414f, 18.697952270507812f, 2.261260986328125f, 24.61199951171875f, 21.778478622436523f, 27.2296085357666f, 5.742082118988037f, 22.343481063842773f, 1.7627668380737305f, 19.587297439575195f, 8.192992210388184f, 6.798495769500732f, 26.264734268188477f, 3.1879794597625732f, 15.670880317687988f, 25.618289947509766f, 7.344959259033203f, 6.31436824798584f, 26.417451858520508f, 12.687529563903809f, 21.508832931518555f, 0.9561920762062073f, 10.870707511901855f, 5.156429767608643f, 20.18296241760254f, 2.487095355987549f, 28.636865615844727f, 0.760341465473175f, 21.882705688476562f, 0.634346067905426f, 7.670701503753662f, 24.400630950927734f, 4.71354866027832f, 5.512164115905762f, 20.744863510131836f, 11.566976547241211f, 1.2948298454284668f, 29.70004653930664f, 4.542603492736816f, 1.0880697965621948f, 10.326029777526855f, 18.457183837890625f, 22.273788452148438f, 3.393447160720825f, 10.116413116455078f, 0.924325704574585f, 13.45959758758545f, 22.979097366333008f, 22.198400497436523f, 27.060604095458984f, 22.669864654541016f, 25.87337303161621f, 21.160354614257812f, 14.183384895324707f, 6.765827178955078f, 19.82485580444336f, 9.489177703857422f, 3.0614731311798096f, 13.434656143188477f, 26.242891311645508f, 3.826093912124634f, 17.54867172241211f, 11.788576126098633f, 15.44408130645752f, 4.314883708953857f, 28.791934967041016f, 7.772892475128174f, 18.18233871459961f, 12.592666625976562f, 0.5409965515136719f, 16.73850440979004f, 4.217081546783447f, 1.7034298181533813f, 1.0066874027252197f, 4.8349504470825195f, 2.8761582374572754f, 19.052270889282227f, 15.247775077819824f, 29.503982543945312f, 28.023908615112305f, 29.835756301879883f, 6.974215030670166f, 13.340923309326172f, 7.523422718048096f, 17.737119674682617f, 18.72492218017578f, 24.006223678588867f, 21.284948348999023f, 7.698278427124023f, 12.690507888793945f, 15.785697937011719f, 0.1447434276342392f, 1.064982295036316f, 12.261792182922363f, 3.3352489471435547f, 21.713090896606445f, 7.22596549987793f, 2.993192672729492f, 5.4528021812438965f, 6.945763111114502f, 6.520608901977539f, 15.622091293334961f, 13.932093620300293f, 9.29178237915039f, 19.252761840820312f, 6.373492240905762f, 27.196880340576172f, 28.89349937438965f, 21.867931365966797f, 13.012016296386719f, 15.345040321350098f, 17.432289123535156f, 1.537042260169983f, 12.540492057800293f, 15.751935958862305f, 5.436751842498779f, 2.813603639602661f, 24.07965660095215f, 10.985519409179688f, 15.57629108428955f, 27.643510818481445f, 18.315309524536133f, 8.687422752380371f, 29.505632400512695f, 11.166801452636719f, 0.5716531276702881f, 20.5593204498291f, 3.0348563194274902f, 9.1776704788208f, 25.218351364135742f, 20.177152633666992f, 0.47166216373443604f, 13.542703628540039f, 12.320231437683105f, 14.575888633728027f, 6.247406959533691f, 17.662351608276367f, 2.213679313659668f, 8.530780792236328f, 11.187063217163086f, 28.05811309814453f, 2.2964465618133545f, 22.64952278137207f, 5.770773887634277f, 17.146581649780273f, 11.753429412841797f, 13.89673137664795f, 22.60741424560547f, 11.851276397705078f, 3.6518843173980713f, 3.6531028747558594f, 2.4153215885162354f, 25.502126693725586f, 19.229747772216797f, 28.790056228637695f, 20.779577255249023f, 0.7400631904602051f, 19.774789810180664f, 23.31635856628418f, 21.705549240112305f, 14.938485145568848f, 10.727538108825684f, 13.711071014404297f, 23.96166229248047f, 8.06827449798584f, 15.789112091064453f, 14.326786041259766f, 28.640905380249023f, 24.1304988861084f, 27.96161651611328f, 25.080167770385742f, 8.902910232543945f, 6.948821067810059f, 14.663683891296387f, 7.78216028213501f, 12.829614639282227f, 20.37420654296875f, 27.55740737915039f, 17.577016830444336f, 24.53559684753418f, 2.8784193992614746f, 10.681716918945312f, 29.93243980407715f, 4.395031452178955f, 12.50304126739502f, 2.0051817893981934f, 2.5844807624816895f, 26.86501121520996f, 29.65911102294922f, 19.442462921142578f, 3.85545015335083f, 8.891475677490234f, 6.950989246368408f, 20.12196922302246f, 20.43297004699707f, 13.165374755859375f, 15.719842910766602f, 3.362107992172241f, 16.226797103881836f, 28.49816131591797f, 22.67331886291504f, 2.884633779525757f, 15.495040893554688f, 21.46094512939453f, 7.717815399169922f, 26.846899032592773f, 13.828228950500488f, 21.09693717956543f, 12.12490177154541f, 29.85399055480957f, 23.484472274780273f, 17.20321273803711f, 4.342950820922852f, 13.23549747467041f, 0.8815472722053528f, 17.85492515563965f, 26.454524993896484f, 5.4127349853515625f, 15.305145263671875f, 14.473750114440918f, 12.147439956665039f, 21.31380271911621f, 28.10009765625f, 21.161775588989258f, 14.174975395202637f, 28.85932159423828f, 9.921825408935547f, 22.368383407592773f, 19.75455093383789f, 22.8482666015625f, 25.562196731567383f, 6.749966621398926f, 18.637470245361328f, 12.081716537475586f, 20.009157180786133f, 29.3170223236084f, 19.044925689697266f, 0.3481738269329071f, 13.936464309692383f, 21.347293853759766f, 26.496627807617188f, 19.50255012512207f, 24.482097625732422f, 0.5141218900680542f, 28.296886444091797f, 21.883909225463867f, 18.19331932067871f, 27.159690856933594f, 26.54039192199707f, 3.013721466064453f, 24.46863555908203f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 4.136193752288818f, 18.36971092224121f, 13.031939506530762f, 7.610733509063721f, 16.982839584350586f, 14.012606620788574f, 6.1499247550964355f, 29.0034236907959f, 2.1847610473632812f, 0.09111864119768143f, 14.56269359588623f, 25.115745544433594f, 19.75206184387207f, 22.640087127685547f, 14.550013542175293f, 20.244070053100586f, 10.046719551086426f, 8.008358001708984f, 15.087020874023438f, 0.8258345127105713f, 2.3942577838897705f, 22.618791580200195f, 5.210988998413086f, 22.507671356201172f}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({23.01002311706543f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 24.125682830810547f, 23.01002311706543f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 24.125682830810547f, 4.136193752288818f, 4.136193752288818f, 18.36971092224121f, 13.031939506530762f, 7.610733509063721f, 16.982839584350586f, 14.012606620788574f, 14.012606620788574f, 6.1499247550964355f, 6.1499247550964355f, 29.0034236907959f, 2.1847610473632812f, 0.09111864119768143f, 14.56269359588623f, 25.115745544433594f, 25.115745544433594f, 19.75206184387207f, 19.75206184387207f, 22.640087127685547f, 14.550013542175293f, 20.244070053100586f, 10.046719551086426f, 8.008358001708984f, 8.008358001708984f, 15.087020874023438f, 15.087020874023438f, 0.8258345127105713f, 2.3942577838897705f, 22.618791580200195f, 5.210988998413086f, 22.507671356201172f, 22.507671356201172f, 15.087020874023438f, 15.087020874023438f, 0.8258345127105713f, 2.3942577838897705f, 22.618791580200195f, 5.210988998413086f, 22.507671356201172f, 22.507671356201172f, 19.75206184387207f, 19.75206184387207f, 22.640087127685547f, 14.550013542175293f, 20.244070053100586f, 10.046719551086426f, 8.008358001708984f, 8.008358001708984f, 6.1499247550964355f, 6.1499247550964355f, 29.0034236907959f, 2.1847610473632812f, 0.09111864119768143f, 14.56269359588623f, 25.115745544433594f, 25.115745544433594f, 4.136193752288818f, 4.136193752288818f, 18.36971092224121f, 13.031939506530762f, 7.610733509063721f, 16.982839584350586f, 14.012606620788574f, 14.012606620788574f, 23.01002311706543f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 24.125682830810547f, 21.31380271911621f, 21.31380271911621f, 28.10009765625f, 21.161775588989258f, 14.174975395202637f, 28.85932159423828f, 9.921825408935547f, 9.921825408935547f, 21.31380271911621f, 21.31380271911621f, 28.10009765625f, 21.161775588989258f, 14.174975395202637f, 28.85932159423828f, 9.921825408935547f, 9.921825408935547f, 22.368383407592773f, 22.368383407592773f, 19.75455093383789f, 22.8482666015625f, 25.562196731567383f, 6.749966621398926f, 18.637470245361328f, 18.637470245361328f, 12.081716537475586f, 12.081716537475586f, 20.009157180786133f, 29.3170223236084f, 19.044925689697266f, 0.3481738269329071f, 13.936464309692383f, 13.936464309692383f, 21.347293853759766f, 21.347293853759766f, 26.496627807617188f, 19.50255012512207f, 24.482097625732422f, 0.5141218900680542f, 28.296886444091797f, 28.296886444091797f, 21.883909225463867f, 21.883909225463867f, 18.19331932067871f, 27.159690856933594f, 26.54039192199707f, 3.013721466064453f, 24.46863555908203f, 24.46863555908203f, 21.883909225463867f, 21.883909225463867f, 18.19331932067871f, 27.159690856933594f, 26.54039192199707f, 3.013721466064453f, 24.46863555908203f, 24.46863555908203f, 21.347293853759766f, 21.347293853759766f, 26.496627807617188f, 19.50255012512207f, 24.482097625732422f, 0.5141218900680542f, 28.296886444091797f, 28.296886444091797f, 12.081716537475586f, 12.081716537475586f, 20.009157180786133f, 29.3170223236084f, 19.044925689697266f, 0.3481738269329071f, 13.936464309692383f, 13.936464309692383f, 22.368383407592773f, 22.368383407592773f, 19.75455093383789f, 22.8482666015625f, 25.562196731567383f, 6.749966621398926f, 18.637470245361328f, 18.637470245361328f, 21.31380271911621f, 21.31380271911621f, 28.10009765625f, 21.161775588989258f, 14.174975395202637f, 28.85932159423828f, 9.921825408935547f, 9.921825408935547f, 8.891475677490234f, 8.891475677490234f, 6.950989246368408f, 20.12196922302246f, 20.43297004699707f, 13.165374755859375f, 15.719842910766602f, 15.719842910766602f, 8.891475677490234f, 8.891475677490234f, 6.950989246368408f, 20.12196922302246f, 20.43297004699707f, 13.165374755859375f, 15.719842910766602f, 15.719842910766602f, 3.362107992172241f, 3.362107992172241f, 16.226797103881836f, 28.49816131591797f, 22.67331886291504f, 2.884633779525757f, 15.495040893554688f, 15.495040893554688f, 21.46094512939453f, 21.46094512939453f, 7.717815399169922f, 26.846899032592773f, 13.828228950500488f, 21.09693717956543f, 12.12490177154541f, 12.12490177154541f, 29.85399055480957f, 29.85399055480957f, 23.484472274780273f, 17.20321273803711f, 4.342950820922852f, 13.23549747467041f, 0.8815472722053528f, 0.8815472722053528f, 17.85492515563965f, 17.85492515563965f, 26.454524993896484f, 5.4127349853515625f, 15.305145263671875f, 14.473750114440918f, 12.147439956665039f, 12.147439956665039f, 17.85492515563965f, 17.85492515563965f, 26.454524993896484f, 5.4127349853515625f, 15.305145263671875f, 14.473750114440918f, 12.147439956665039f, 12.147439956665039f, 29.85399055480957f, 29.85399055480957f, 23.484472274780273f, 17.20321273803711f, 4.342950820922852f, 13.23549747467041f, 0.8815472722053528f, 0.8815472722053528f, 21.46094512939453f, 21.46094512939453f, 7.717815399169922f, 26.846899032592773f, 13.828228950500488f, 21.09693717956543f, 12.12490177154541f, 12.12490177154541f, 3.362107992172241f, 3.362107992172241f, 16.226797103881836f, 28.49816131591797f, 22.67331886291504f, 2.884633779525757f, 15.495040893554688f, 15.495040893554688f, 8.891475677490234f, 8.891475677490234f, 6.950989246368408f, 20.12196922302246f, 20.43297004699707f, 13.165374755859375f, 15.719842910766602f, 15.719842910766602f, 10.727538108825684f, 10.727538108825684f, 13.711071014404297f, 23.96166229248047f, 8.06827449798584f, 15.789112091064453f, 14.326786041259766f, 14.326786041259766f, 10.727538108825684f, 10.727538108825684f, 13.711071014404297f, 23.96166229248047f, 8.06827449798584f, 15.789112091064453f, 14.326786041259766f, 14.326786041259766f, 28.640905380249023f, 28.640905380249023f, 24.1304988861084f, 27.96161651611328f, 25.080167770385742f, 8.902910232543945f, 6.948821067810059f, 6.948821067810059f, 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12.687529563903809f, 21.508832931518555f, 0.9561920762062073f, 10.870707511901855f, 10.870707511901855f, 6.798495769500732f, 6.798495769500732f, 26.264734268188477f, 3.1879794597625732f, 15.670880317687988f, 25.618289947509766f, 7.344959259033203f, 7.344959259033203f, 21.71318817138672f, 21.71318817138672f, 14.598257064819336f, 6.654330253601074f, 9.74001693725586f, 20.98714828491211f, 4.982090473175049f, 4.982090473175049f, 21.71318817138672f, 21.71318817138672f, 14.598257064819336f, 6.654330253601074f, 9.74001693725586f, 20.98714828491211f, 4.982090473175049f, 4.982090473175049f, 27.23821449279785f, 27.23821449279785f, 8.0441255569458f, 27.34133529663086f, 9.286893844604492f, 28.72085189819336f, 21.186174392700195f, 21.186174392700195f, 15.127464294433594f, 15.127464294433594f, 15.532432556152344f, 19.54243278503418f, 17.638341903686523f, 9.355329513549805f, 6.234554290771484f, 6.234554290771484f, 15.356749534606934f, 15.356749534606934f, 28.02463150024414f, 18.697952270507812f, 2.261260986328125f, 24.61199951171875f, 21.778478622436523f, 21.778478622436523f, 27.2296085357666f, 27.2296085357666f, 5.742082118988037f, 22.343481063842773f, 1.7627668380737305f, 19.587297439575195f, 8.192992210388184f, 8.192992210388184f, 27.2296085357666f, 27.2296085357666f, 5.742082118988037f, 22.343481063842773f, 1.7627668380737305f, 19.587297439575195f, 8.192992210388184f, 8.192992210388184f, 15.356749534606934f, 15.356749534606934f, 28.02463150024414f, 18.697952270507812f, 2.261260986328125f, 24.61199951171875f, 21.778478622436523f, 21.778478622436523f, 15.127464294433594f, 15.127464294433594f, 15.532432556152344f, 19.54243278503418f, 17.638341903686523f, 9.355329513549805f, 6.234554290771484f, 6.234554290771484f, 27.23821449279785f, 27.23821449279785f, 8.0441255569458f, 27.34133529663086f, 9.286893844604492f, 28.72085189819336f, 21.186174392700195f, 21.186174392700195f, 21.71318817138672f, 21.71318817138672f, 14.598257064819336f, 6.654330253601074f, 9.74001693725586f, 20.98714828491211f, 4.982090473175049f, 4.982090473175049f}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_float16_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_three_symmetric_float16_all_tensors_as_inputs", get_test_model_three_symmetric_float16_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_float16_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({23.01002311706543f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 24.125682830810547f, 23.01002311706543f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 24.125682830810547f, 4.136193752288818f, 4.136193752288818f, 18.36971092224121f, 13.031939506530762f, 7.610733509063721f, 16.982839584350586f, 14.012606620788574f, 14.012606620788574f, 6.1499247550964355f, 6.1499247550964355f, 29.0034236907959f, 2.1847610473632812f, 0.09111864119768143f, 14.56269359588623f, 25.115745544433594f, 25.115745544433594f, 19.75206184387207f, 19.75206184387207f, 22.640087127685547f, 14.550013542175293f, 20.244070053100586f, 10.046719551086426f, 8.008358001708984f, 8.008358001708984f, 15.087020874023438f, 15.087020874023438f, 0.8258345127105713f, 2.3942577838897705f, 22.618791580200195f, 5.210988998413086f, 22.507671356201172f, 22.507671356201172f, 15.087020874023438f, 15.087020874023438f, 0.8258345127105713f, 2.3942577838897705f, 22.618791580200195f, 5.210988998413086f, 22.507671356201172f, 22.507671356201172f, 19.75206184387207f, 19.75206184387207f, 22.640087127685547f, 14.550013542175293f, 20.244070053100586f, 10.046719551086426f, 8.008358001708984f, 8.008358001708984f, 6.1499247550964355f, 6.1499247550964355f, 29.0034236907959f, 2.1847610473632812f, 0.09111864119768143f, 14.56269359588623f, 25.115745544433594f, 25.115745544433594f, 4.136193752288818f, 4.136193752288818f, 18.36971092224121f, 13.031939506530762f, 7.610733509063721f, 16.982839584350586f, 14.012606620788574f, 14.012606620788574f, 23.01002311706543f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 24.125682830810547f, 21.31380271911621f, 21.31380271911621f, 28.10009765625f, 21.161775588989258f, 14.174975395202637f, 28.85932159423828f, 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15.719842910766602f, 3.362107992172241f, 3.362107992172241f, 16.226797103881836f, 28.49816131591797f, 22.67331886291504f, 2.884633779525757f, 15.495040893554688f, 15.495040893554688f, 21.46094512939453f, 21.46094512939453f, 7.717815399169922f, 26.846899032592773f, 13.828228950500488f, 21.09693717956543f, 12.12490177154541f, 12.12490177154541f, 29.85399055480957f, 29.85399055480957f, 23.484472274780273f, 17.20321273803711f, 4.342950820922852f, 13.23549747467041f, 0.8815472722053528f, 0.8815472722053528f, 17.85492515563965f, 17.85492515563965f, 26.454524993896484f, 5.4127349853515625f, 15.305145263671875f, 14.473750114440918f, 12.147439956665039f, 12.147439956665039f, 17.85492515563965f, 17.85492515563965f, 26.454524993896484f, 5.4127349853515625f, 15.305145263671875f, 14.473750114440918f, 12.147439956665039f, 12.147439956665039f, 29.85399055480957f, 29.85399055480957f, 23.484472274780273f, 17.20321273803711f, 4.342950820922852f, 13.23549747467041f, 0.8815472722053528f, 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20.98714828491211f, 4.982090473175049f, 4.982090473175049f}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // in4_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({28.681028366088867f, 28.434823989868164f, 1.6965410709381104f, 2.5461597442626953f, 25.064966201782227f, 22.079099655151367f, 20.09191131591797f, 9.244093894958496f, 18.178325653076172f, 18.204051971435547f, 17.436120986938477f, 4.751486301422119f, 12.920088768005371f, 11.805954933166504f, 21.69036293029785f, 29.844587326049805f, 28.48186492919922f, 16.3253116607666f, 13.345625877380371f, 8.047222137451172f, 1.0777299404144287f, 0.8233457207679749f, 13.946815490722656f, 9.553954124450684f, 11.400447845458984f, 26.75368309020996f, 15.7725830078125f, 16.815311431884766f, 7.083702087402344f, 0.7157423496246338f, 9.754287719726562f, 4.100921630859375f, 15.30671501159668f, 29.960506439208984f, 20.234390258789062f, 5.455305099487305f, 26.807146072387695f, 23.90279769897461f, 22.03205108642578f, 27.19780921936035f, 22.886564254760742f, 23.692428588867188f, 10.613609313964844f, 29.429296493530273f, 28.85702896118164f, 4.835539817810059f, 22.6201229095459f, 21.454526901245117f, 13.842201232910156f, 15.91067123413086f, 14.700417518615723f, 27.744962692260742f, 15.025232315063477f, 24.94573402404785f, 10.61772632598877f, 26.48552703857422f, 26.991018295288086f, 13.830365180969238f, 17.031152725219727f, 27.609912872314453f, 21.71318817138672f, 14.598257064819336f, 6.654330253601074f, 9.74001693725586f, 20.98714828491211f, 4.982090473175049f, 27.23821449279785f, 8.0441255569458f, 27.34133529663086f, 9.286893844604492f, 28.72085189819336f, 21.186174392700195f, 15.127464294433594f, 15.532432556152344f, 19.54243278503418f, 17.638341903686523f, 9.355329513549805f, 6.234554290771484f, 15.356749534606934f, 28.02463150024414f, 18.697952270507812f, 2.261260986328125f, 24.61199951171875f, 21.778478622436523f, 27.2296085357666f, 5.742082118988037f, 22.343481063842773f, 1.7627668380737305f, 19.587297439575195f, 8.192992210388184f, 6.798495769500732f, 26.264734268188477f, 3.1879794597625732f, 15.670880317687988f, 25.618289947509766f, 7.344959259033203f, 6.31436824798584f, 26.417451858520508f, 12.687529563903809f, 21.508832931518555f, 0.9561920762062073f, 10.870707511901855f, 5.156429767608643f, 20.18296241760254f, 2.487095355987549f, 28.636865615844727f, 0.760341465473175f, 21.882705688476562f, 0.634346067905426f, 7.670701503753662f, 24.400630950927734f, 4.71354866027832f, 5.512164115905762f, 20.744863510131836f, 11.566976547241211f, 1.2948298454284668f, 29.70004653930664f, 4.542603492736816f, 1.0880697965621948f, 10.326029777526855f, 18.457183837890625f, 22.273788452148438f, 3.393447160720825f, 10.116413116455078f, 0.924325704574585f, 13.45959758758545f, 22.979097366333008f, 22.198400497436523f, 27.060604095458984f, 22.669864654541016f, 25.87337303161621f, 21.160354614257812f, 14.183384895324707f, 6.765827178955078f, 19.82485580444336f, 9.489177703857422f, 3.0614731311798096f, 13.434656143188477f, 26.242891311645508f, 3.826093912124634f, 17.54867172241211f, 11.788576126098633f, 15.44408130645752f, 4.314883708953857f, 28.791934967041016f, 7.772892475128174f, 18.18233871459961f, 12.592666625976562f, 0.5409965515136719f, 16.73850440979004f, 4.217081546783447f, 1.7034298181533813f, 1.0066874027252197f, 4.8349504470825195f, 2.8761582374572754f, 19.052270889282227f, 15.247775077819824f, 29.503982543945312f, 28.023908615112305f, 29.835756301879883f, 6.974215030670166f, 13.340923309326172f, 7.523422718048096f, 17.737119674682617f, 18.72492218017578f, 24.006223678588867f, 21.284948348999023f, 7.698278427124023f, 12.690507888793945f, 15.785697937011719f, 0.1447434276342392f, 1.064982295036316f, 12.261792182922363f, 3.3352489471435547f, 21.713090896606445f, 7.22596549987793f, 2.993192672729492f, 5.4528021812438965f, 6.945763111114502f, 6.520608901977539f, 15.622091293334961f, 13.932093620300293f, 9.29178237915039f, 19.252761840820312f, 6.373492240905762f, 27.196880340576172f, 28.89349937438965f, 21.867931365966797f, 13.012016296386719f, 15.345040321350098f, 17.432289123535156f, 1.537042260169983f, 12.540492057800293f, 15.751935958862305f, 5.436751842498779f, 2.813603639602661f, 24.07965660095215f, 10.985519409179688f, 15.57629108428955f, 27.643510818481445f, 18.315309524536133f, 8.687422752380371f, 29.505632400512695f, 11.166801452636719f, 0.5716531276702881f, 20.5593204498291f, 3.0348563194274902f, 9.1776704788208f, 25.218351364135742f, 20.177152633666992f, 0.47166216373443604f, 13.542703628540039f, 12.320231437683105f, 14.575888633728027f, 6.247406959533691f, 17.662351608276367f, 2.213679313659668f, 8.530780792236328f, 11.187063217163086f, 28.05811309814453f, 2.2964465618133545f, 22.64952278137207f, 5.770773887634277f, 17.146581649780273f, 11.753429412841797f, 13.89673137664795f, 22.60741424560547f, 11.851276397705078f, 3.6518843173980713f, 3.6531028747558594f, 2.4153215885162354f, 25.502126693725586f, 19.229747772216797f, 28.790056228637695f, 20.779577255249023f, 0.7400631904602051f, 19.774789810180664f, 23.31635856628418f, 21.705549240112305f, 14.938485145568848f, 10.727538108825684f, 13.711071014404297f, 23.96166229248047f, 8.06827449798584f, 15.789112091064453f, 14.326786041259766f, 28.640905380249023f, 24.1304988861084f, 27.96161651611328f, 25.080167770385742f, 8.902910232543945f, 6.948821067810059f, 14.663683891296387f, 7.78216028213501f, 12.829614639282227f, 20.37420654296875f, 27.55740737915039f, 17.577016830444336f, 24.53559684753418f, 2.8784193992614746f, 10.681716918945312f, 29.93243980407715f, 4.395031452178955f, 12.50304126739502f, 2.0051817893981934f, 2.5844807624816895f, 26.86501121520996f, 29.65911102294922f, 19.442462921142578f, 3.85545015335083f, 8.891475677490234f, 6.950989246368408f, 20.12196922302246f, 20.43297004699707f, 13.165374755859375f, 15.719842910766602f, 3.362107992172241f, 16.226797103881836f, 28.49816131591797f, 22.67331886291504f, 2.884633779525757f, 15.495040893554688f, 21.46094512939453f, 7.717815399169922f, 26.846899032592773f, 13.828228950500488f, 21.09693717956543f, 12.12490177154541f, 29.85399055480957f, 23.484472274780273f, 17.20321273803711f, 4.342950820922852f, 13.23549747467041f, 0.8815472722053528f, 17.85492515563965f, 26.454524993896484f, 5.4127349853515625f, 15.305145263671875f, 14.473750114440918f, 12.147439956665039f, 21.31380271911621f, 28.10009765625f, 21.161775588989258f, 14.174975395202637f, 28.85932159423828f, 9.921825408935547f, 22.368383407592773f, 19.75455093383789f, 22.8482666015625f, 25.562196731567383f, 6.749966621398926f, 18.637470245361328f, 12.081716537475586f, 20.009157180786133f, 29.3170223236084f, 19.044925689697266f, 0.3481738269329071f, 13.936464309692383f, 21.347293853759766f, 26.496627807617188f, 19.50255012512207f, 24.482097625732422f, 0.5141218900680542f, 28.296886444091797f, 21.883909225463867f, 18.19331932067871f, 27.159690856933594f, 26.54039192199707f, 3.013721466064453f, 24.46863555908203f, 23.01002311706543f, 5.986141204833984f, 22.32737159729004f, 17.586822509765625f, 5.744832515716553f, 24.125682830810547f, 4.136193752288818f, 18.36971092224121f, 13.031939506530762f, 7.610733509063721f, 16.982839584350586f, 14.012606620788574f, 6.1499247550964355f, 29.0034236907959f, 2.1847610473632812f, 0.09111864119768143f, 14.56269359588623f, 25.115745544433594f, 19.75206184387207f, 22.640087127685547f, 14.550013542175293f, 20.244070053100586f, 10.046719551086426f, 8.008358001708984f, 15.087020874023438f, 0.8258345127105713f, 2.3942577838897705f, 22.618791580200195f, 5.210988998413086f, 22.507671356201172f}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // placeholder19
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // param24
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_float16_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_three_symmetric_float16_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_three_symmetric_float16_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_quant8_asymm() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({233, 231, 18, 24, 205, 181, 165, 78, 149, 150, 143, 42, 107, 98, 178, 243, 232, 135, 111, 68, 13, 11, 116, 80, 95, 218, 130, 139, 61, 10, 82, 37, 126, 244, 166, 48, 218, 195, 180, 222, 187, 194, 89, 239, 235, 43, 185, 176, 115, 131, 122, 226, 124, 204, 89, 216, 220, 115, 140, 225, 178, 121, 57, 82, 172, 44, 222, 68, 223, 78, 234, 173, 125, 128, 160, 145, 79, 54, 127, 228, 154, 22, 201, 178, 222, 50, 183, 18, 161, 70, 58, 214, 30, 129, 209, 63, 55, 215, 106, 176, 12, 91, 45, 165, 24, 233, 10, 179, 9, 65, 199, 42, 48, 170, 97, 14, 242, 40, 13, 87, 152, 182, 31, 85, 11, 112, 188, 182, 220, 185, 211, 173, 117, 58, 163, 80, 28, 111, 214, 35, 144, 98, 128, 39, 234, 66, 149, 105, 8, 138, 38, 18, 12, 43, 27, 156, 126, 240, 228, 243, 60, 111, 64, 146, 154, 196, 174, 66, 106, 130, 5, 13, 102, 31, 178, 62, 28, 48, 60, 56, 129, 115, 78, 158, 55, 222, 235, 179, 108, 127, 143, 16, 104, 130, 47, 27, 197, 92, 129, 225, 151, 73, 240, 93, 9, 168, 28, 77, 206, 165, 8, 112, 103, 121, 54, 145, 22, 72, 93, 228, 22, 185, 50, 141, 98, 115, 185, 99, 33, 33, 23, 208, 158, 234, 170, 10, 162, 191, 178, 124, 90, 114, 196, 69, 130, 119, 233, 197, 228, 205, 75, 60, 121, 66, 107, 167, 224, 145, 200, 27, 89, 243, 39, 104, 20, 25, 219, 241, 160, 35, 75, 60, 165, 167, 109, 130, 31, 134, 232, 185, 27, 128, 176, 66, 219, 115, 173, 101, 243, 192, 142, 39, 110, 11, 147, 216, 47, 126, 120, 101, 175, 229, 173, 117, 235, 83, 183, 162, 187, 208, 58, 153, 101, 164, 239, 156, 7, 115, 175, 216, 160, 200, 8, 230, 179, 150, 221, 216, 28, 200, 188, 52, 183, 145, 50, 197, 37, 151, 108, 65, 140, 116, 53, 236, 21, 5, 121, 205, 162, 185, 120, 166, 84, 68, 125, 11, 23, 185, 46, 184}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 75, 75, 60, 165, 167, 109, 130, 130, 75, 75, 60, 165, 167, 109, 130, 130, 31, 31, 134, 232, 185, 27, 128, 128, 176, 176, 66, 219, 115, 173, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 147, 147, 216, 47, 126, 120, 101, 101, 147, 147, 216, 47, 126, 120, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 176, 176, 66, 219, 115, 173, 101, 101, 31, 31, 134, 232, 185, 27, 128, 128, 75, 75, 60, 165, 167, 109, 130, 130, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 233, 233, 197, 228, 205, 75, 60, 60, 121, 121, 66, 107, 167, 224, 145, 145, 200, 200, 27, 89, 243, 39, 104, 104, 20, 20, 25, 219, 241, 160, 35, 35, 20, 20, 25, 219, 241, 160, 35, 35, 200, 200, 27, 89, 243, 39, 104, 104, 121, 121, 66, 107, 167, 224, 145, 145, 233, 233, 197, 228, 205, 75, 60, 60, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 233, 233, 197, 228, 205, 75, 60, 60, 121, 121, 66, 107, 167, 224, 145, 145, 200, 200, 27, 89, 243, 39, 104, 104, 20, 20, 25, 219, 241, 160, 35, 35, 20, 20, 25, 219, 241, 160, 35, 35, 200, 200, 27, 89, 243, 39, 104, 104, 121, 121, 66, 107, 167, 224, 145, 145, 233, 233, 197, 228, 205, 75, 60, 60, 90, 90, 114, 196, 69, 130, 119, 119, 75, 75, 60, 165, 167, 109, 130, 130, 75, 75, 60, 165, 167, 109, 130, 130, 31, 31, 134, 232, 185, 27, 128, 128, 176, 176, 66, 219, 115, 173, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 147, 147, 216, 47, 126, 120, 101, 101, 147, 147, 216, 47, 126, 120, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 176, 176, 66, 219, 115, 173, 101, 101, 31, 31, 134, 232, 185, 27, 128, 128, 75, 75, 60, 165, 167, 109, 130, 130, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 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173, 117, 235, 83, 83, 75, 75, 60, 165, 167, 109, 130, 130, 75, 75, 60, 165, 167, 109, 130, 130, 31, 31, 134, 232, 185, 27, 128, 128, 176, 176, 66, 219, 115, 173, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 147, 147, 216, 47, 126, 120, 101, 101, 147, 147, 216, 47, 126, 120, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 176, 176, 66, 219, 115, 173, 101, 101, 31, 31, 134, 232, 185, 27, 128, 128, 75, 75, 60, 165, 167, 109, 130, 130, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 233, 233, 197, 228, 205, 75, 60, 60, 121, 121, 66, 107, 167, 224, 145, 145, 200, 200, 27, 89, 243, 39, 104, 104, 20, 20, 25, 219, 241, 160, 35, 35, 20, 20, 25, 219, 241, 160, 35, 35, 200, 200, 27, 89, 243, 39, 104, 104, 121, 121, 66, 107, 167, 224, 145, 145, 233, 233, 197, 228, 205, 75, 60, 60, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 233, 233, 197, 228, 205, 75, 60, 60, 121, 121, 66, 107, 167, 224, 145, 145, 200, 200, 27, 89, 243, 39, 104, 104, 20, 20, 25, 219, 241, 160, 35, 35, 20, 20, 25, 219, 241, 160, 35, 35, 200, 200, 27, 89, 243, 39, 104, 104, 121, 121, 66, 107, 167, 224, 145, 145, 233, 233, 197, 228, 205, 75, 60, 60, 90, 90, 114, 196, 69, 130, 119, 119, 75, 75, 60, 165, 167, 109, 130, 130, 75, 75, 60, 165, 167, 109, 130, 130, 31, 31, 134, 232, 185, 27, 128, 128, 176, 176, 66, 219, 115, 173, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 147, 147, 216, 47, 126, 120, 101, 101, 147, 147, 216, 47, 126, 120, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 176, 176, 66, 219, 115, 173, 101, 101, 31, 31, 134, 232, 185, 27, 128, 128, 75, 75, 60, 165, 167, 109, 130, 130, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 75, 75, 60, 165, 167, 109, 130, 130, 75, 75, 60, 165, 167, 109, 130, 130, 31, 31, 134, 232, 185, 27, 128, 128, 176, 176, 66, 219, 115, 173, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 147, 147, 216, 47, 126, 120, 101, 101, 147, 147, 216, 47, 126, 120, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 176, 176, 66, 219, 115, 173, 101, 101, 31, 31, 134, 232, 185, 27, 128, 128, 75, 75, 60, 165, 167, 109, 130, 130, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 233, 233, 197, 228, 205, 75, 60, 60, 121, 121, 66, 107, 167, 224, 145, 145, 200, 200, 27, 89, 243, 39, 104, 104, 20, 20, 25, 219, 241, 160, 35, 35, 20, 20, 25, 219, 241, 160, 35, 35, 200, 200, 27, 89, 243, 39, 104, 104, 121, 121, 66, 107, 167, 224, 145, 145, 233, 233, 197, 228, 205, 75, 60, 60, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 233, 233, 197, 228, 205, 75, 60, 60, 121, 121, 66, 107, 167, 224, 145, 145, 200, 200, 27, 89, 243, 39, 104, 104, 20, 20, 25, 219, 241, 160, 35, 35, 20, 20, 25, 219, 241, 160, 35, 35, 200, 200, 27, 89, 243, 39, 104, 104, 121, 121, 66, 107, 167, 224, 145, 145, 233, 233, 197, 228, 205, 75, 60, 60, 90, 90, 114, 196, 69, 130, 119, 119, 75, 75, 60, 165, 167, 109, 130, 130, 75, 75, 60, 165, 167, 109, 130, 130, 31, 31, 134, 232, 185, 27, 128, 128, 176, 176, 66, 219, 115, 173, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 147, 147, 216, 47, 126, 120, 101, 101, 147, 147, 216, 47, 126, 120, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 176, 176, 66, 219, 115, 173, 101, 101, 31, 31, 134, 232, 185, 27, 128, 128, 75, 75, 60, 165, 167, 109, 130, 130, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 8, 8, 112, 103, 121, 54, 145, 145, 8, 8, 112, 103, 121, 54, 145, 145, 22, 22, 72, 93, 228, 22, 185, 185, 50, 50, 141, 98, 115, 185, 99, 99, 33, 33, 33, 23, 208, 158, 234, 234, 170, 170, 10, 162, 191, 178, 124, 124, 170, 170, 10, 162, 191, 178, 124, 124, 33, 33, 33, 23, 208, 158, 234, 234, 50, 50, 141, 98, 115, 185, 99, 99, 22, 22, 72, 93, 228, 22, 185, 185, 8, 8, 112, 103, 121, 54, 145, 145, 129, 129, 115, 78, 158, 55, 222, 222, 129, 129, 115, 78, 158, 55, 222, 222, 235, 235, 179, 108, 127, 143, 16, 16, 104, 104, 130, 47, 27, 197, 92, 92, 129, 129, 225, 151, 73, 240, 93, 93, 9, 9, 168, 28, 77, 206, 165, 165, 9, 9, 168, 28, 77, 206, 165, 165, 129, 129, 225, 151, 73, 240, 93, 93, 104, 104, 130, 47, 27, 197, 92, 92, 235, 235, 179, 108, 127, 143, 16, 16, 129, 129, 115, 78, 158, 55, 222, 222, 38, 38, 18, 12, 43, 27, 156, 156, 38, 38, 18, 12, 43, 27, 156, 156, 126, 126, 240, 228, 243, 60, 111, 111, 64, 64, 146, 154, 196, 174, 66, 66, 106, 106, 130, 5, 13, 102, 31, 31, 178, 178, 62, 28, 48, 60, 56, 56, 178, 178, 62, 28, 48, 60, 56, 56, 106, 106, 130, 5, 13, 102, 31, 31, 64, 64, 146, 154, 196, 174, 66, 66, 126, 126, 240, 228, 243, 60, 111, 111, 38, 38, 18, 12, 43, 27, 156, 156, 152, 152, 182, 31, 85, 11, 112, 112, 152, 152, 182, 31, 85, 11, 112, 112, 188, 188, 182, 220, 185, 211, 173, 173, 117, 117, 58, 163, 80, 28, 111, 111, 214, 214, 35, 144, 98, 128, 39, 39, 234, 234, 66, 149, 105, 8, 138, 138, 234, 234, 66, 149, 105, 8, 138, 138, 214, 214, 35, 144, 98, 128, 39, 39, 117, 117, 58, 163, 80, 28, 111, 111, 188, 188, 182, 220, 185, 211, 173, 173, 152, 152, 182, 31, 85, 11, 112, 112, 152, 152, 182, 31, 85, 11, 112, 112, 152, 152, 182, 31, 85, 11, 112, 112, 188, 188, 182, 220, 185, 211, 173, 173, 117, 117, 58, 163, 80, 28, 111, 111, 214, 214, 35, 144, 98, 128, 39, 39, 234, 234, 66, 149, 105, 8, 138, 138, 234, 234, 66, 149, 105, 8, 138, 138, 214, 214, 35, 144, 98, 128, 39, 39, 117, 117, 58, 163, 80, 28, 111, 111, 188, 188, 182, 220, 185, 211, 173, 173, 152, 152, 182, 31, 85, 11, 112, 112, 38, 38, 18, 12, 43, 27, 156, 156, 38, 38, 18, 12, 43, 27, 156, 156, 126, 126, 240, 228, 243, 60, 111, 111, 64, 64, 146, 154, 196, 174, 66, 66, 106, 106, 130, 5, 13, 102, 31, 31, 178, 178, 62, 28, 48, 60, 56, 56, 178, 178, 62, 28, 48, 60, 56, 56, 106, 106, 130, 5, 13, 102, 31, 31, 64, 64, 146, 154, 196, 174, 66, 66, 126, 126, 240, 228, 243, 60, 111, 111, 38, 38, 18, 12, 43, 27, 156, 156, 129, 129, 115, 78, 158, 55, 222, 222, 129, 129, 115, 78, 158, 55, 222, 222, 235, 235, 179, 108, 127, 143, 16, 16, 104, 104, 130, 47, 27, 197, 92, 92, 129, 129, 225, 151, 73, 240, 93, 93, 9, 9, 168, 28, 77, 206, 165, 165, 9, 9, 168, 28, 77, 206, 165, 165, 129, 129, 225, 151, 73, 240, 93, 93, 104, 104, 130, 47, 27, 197, 92, 92, 235, 235, 179, 108, 127, 143, 16, 16, 129, 129, 115, 78, 158, 55, 222, 222, 8, 8, 112, 103, 121, 54, 145, 145, 8, 8, 112, 103, 121, 54, 145, 145, 22, 22, 72, 93, 228, 22, 185, 185, 50, 50, 141, 98, 115, 185, 99, 99, 33, 33, 33, 23, 208, 158, 234, 234, 170, 170, 10, 162, 191, 178, 124, 124, 170, 170, 10, 162, 191, 178, 124, 124, 33, 33, 33, 23, 208, 158, 234, 234, 50, 50, 141, 98, 115, 185, 99, 99, 22, 22, 72, 93, 228, 22, 185, 185, 8, 8, 112, 103, 121, 54, 145, 145, 8, 8, 112, 103, 121, 54, 145, 145, 8, 8, 112, 103, 121, 54, 145, 145, 22, 22, 72, 93, 228, 22, 185, 185, 50, 50, 141, 98, 115, 185, 99, 99, 33, 33, 33, 23, 208, 158, 234, 234, 170, 170, 10, 162, 191, 178, 124, 124, 170, 170, 10, 162, 191, 178, 124, 124, 33, 33, 33, 23, 208, 158, 234, 234, 50, 50, 141, 98, 115, 185, 99, 99, 22, 22, 72, 93, 228, 22, 185, 185, 8, 8, 112, 103, 121, 54, 145, 145, 129, 129, 115, 78, 158, 55, 222, 222, 129, 129, 115, 78, 158, 55, 222, 222, 235, 235, 179, 108, 127, 143, 16, 16, 104, 104, 130, 47, 27, 197, 92, 92, 129, 129, 225, 151, 73, 240, 93, 93, 9, 9, 168, 28, 77, 206, 165, 165, 9, 9, 168, 28, 77, 206, 165, 165, 129, 129, 225, 151, 73, 240, 93, 93, 104, 104, 130, 47, 27, 197, 92, 92, 235, 235, 179, 108, 127, 143, 16, 16, 129, 129, 115, 78, 158, 55, 222, 222, 58, 58, 214, 30, 129, 209, 63, 63, 58, 58, 214, 30, 129, 209, 63, 63, 55, 55, 215, 106, 176, 12, 91, 91, 45, 45, 165, 24, 233, 10, 179, 179, 9, 9, 65, 199, 42, 48, 170, 170, 97, 97, 14, 242, 40, 13, 87, 87, 97, 97, 14, 242, 40, 13, 87, 87, 9, 9, 65, 199, 42, 48, 170, 170, 45, 45, 165, 24, 233, 10, 179, 179, 55, 55, 215, 106, 176, 12, 91, 91, 58, 58, 214, 30, 129, 209, 63, 63, 178, 178, 121, 57, 82, 172, 44, 44, 178, 178, 121, 57, 82, 172, 44, 44, 222, 222, 68, 223, 78, 234, 173, 173, 125, 125, 128, 160, 145, 79, 54, 54, 127, 127, 228, 154, 22, 201, 178, 178, 222, 222, 50, 183, 18, 161, 70, 70, 222, 222, 50, 183, 18, 161, 70, 70, 127, 127, 228, 154, 22, 201, 178, 178, 125, 125, 128, 160, 145, 79, 54, 54, 222, 222, 68, 223, 78, 234, 173, 173, 178, 178, 121, 57, 82, 172, 44, 44, 82, 82, 37, 126, 244, 166, 48, 48, 82, 82, 37, 126, 244, 166, 48, 48, 218, 218, 195, 180, 222, 187, 194, 194, 89, 89, 239, 235, 43, 185, 176, 176, 115, 115, 131, 122, 226, 124, 204, 204, 89, 89, 216, 220, 115, 140, 225, 225, 89, 89, 216, 220, 115, 140, 225, 225, 115, 115, 131, 122, 226, 124, 204, 204, 89, 89, 239, 235, 43, 185, 176, 176, 218, 218, 195, 180, 222, 187, 194, 194, 82, 82, 37, 126, 244, 166, 48, 48, 233, 233, 231, 18, 24, 205, 181, 181, 233, 233, 231, 18, 24, 205, 181, 181, 165, 165, 78, 149, 150, 143, 42, 42, 107, 107, 98, 178, 243, 232, 135, 135, 111, 111, 68, 13, 11, 116, 80, 80, 95, 95, 218, 130, 139, 61, 10, 10, 95, 95, 218, 130, 139, 61, 10, 10, 111, 111, 68, 13, 11, 116, 80, 80, 107, 107, 98, 178, 243, 232, 135, 135, 165, 165, 78, 149, 150, 143, 42, 42, 233, 233, 231, 18, 24, 205, 181, 181, 233, 233, 231, 18, 24, 205, 181, 181, 233, 233, 231, 18, 24, 205, 181, 181, 165, 165, 78, 149, 150, 143, 42, 42, 107, 107, 98, 178, 243, 232, 135, 135, 111, 111, 68, 13, 11, 116, 80, 80, 95, 95, 218, 130, 139, 61, 10, 10, 95, 95, 218, 130, 139, 61, 10, 10, 111, 111, 68, 13, 11, 116, 80, 80, 107, 107, 98, 178, 243, 232, 135, 135, 165, 165, 78, 149, 150, 143, 42, 42, 233, 233, 231, 18, 24, 205, 181, 181, 82, 82, 37, 126, 244, 166, 48, 48, 82, 82, 37, 126, 244, 166, 48, 48, 218, 218, 195, 180, 222, 187, 194, 194, 89, 89, 239, 235, 43, 185, 176, 176, 115, 115, 131, 122, 226, 124, 204, 204, 89, 89, 216, 220, 115, 140, 225, 225, 89, 89, 216, 220, 115, 140, 225, 225, 115, 115, 131, 122, 226, 124, 204, 204, 89, 89, 239, 235, 43, 185, 176, 176, 218, 218, 195, 180, 222, 187, 194, 194, 82, 82, 37, 126, 244, 166, 48, 48, 178, 178, 121, 57, 82, 172, 44, 44, 178, 178, 121, 57, 82, 172, 44, 44, 222, 222, 68, 223, 78, 234, 173, 173, 125, 125, 128, 160, 145, 79, 54, 54, 127, 127, 228, 154, 22, 201, 178, 178, 222, 222, 50, 183, 18, 161, 70, 70, 222, 222, 50, 183, 18, 161, 70, 70, 127, 127, 228, 154, 22, 201, 178, 178, 125, 125, 128, 160, 145, 79, 54, 54, 222, 222, 68, 223, 78, 234, 173, 173, 178, 178, 121, 57, 82, 172, 44, 44, 58, 58, 214, 30, 129, 209, 63, 63, 58, 58, 214, 30, 129, 209, 63, 63, 55, 55, 215, 106, 176, 12, 91, 91, 45, 45, 165, 24, 233, 10, 179, 179, 9, 9, 65, 199, 42, 48, 170, 170, 97, 97, 14, 242, 40, 13, 87, 87, 97, 97, 14, 242, 40, 13, 87, 87, 9, 9, 65, 199, 42, 48, 170, 170, 45, 45, 165, 24, 233, 10, 179, 179, 55, 55, 215, 106, 176, 12, 91, 91, 58, 58, 214, 30, 129, 209, 63, 63, 58, 58, 214, 30, 129, 209, 63, 63, 58, 58, 214, 30, 129, 209, 63, 63, 55, 55, 215, 106, 176, 12, 91, 91, 45, 45, 165, 24, 233, 10, 179, 179, 9, 9, 65, 199, 42, 48, 170, 170, 97, 97, 14, 242, 40, 13, 87, 87, 97, 97, 14, 242, 40, 13, 87, 87, 9, 9, 65, 199, 42, 48, 170, 170, 45, 45, 165, 24, 233, 10, 179, 179, 55, 55, 215, 106, 176, 12, 91, 91, 58, 58, 214, 30, 129, 209, 63, 63, 178, 178, 121, 57, 82, 172, 44, 44, 178, 178, 121, 57, 82, 172, 44, 44, 222, 222, 68, 223, 78, 234, 173, 173, 125, 125, 128, 160, 145, 79, 54, 54, 127, 127, 228, 154, 22, 201, 178, 178, 222, 222, 50, 183, 18, 161, 70, 70, 222, 222, 50, 183, 18, 161, 70, 70, 127, 127, 228, 154, 22, 201, 178, 178, 125, 125, 128, 160, 145, 79, 54, 54, 222, 222, 68, 223, 78, 234, 173, 173, 178, 178, 121, 57, 82, 172, 44, 44}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_quant8_asymm = TestModelManager::get().add("mirror_pad_three_symmetric_quant8_asymm", get_test_model_three_symmetric_quant8_asymm());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_quant8_asymm_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 75, 75, 60, 165, 167, 109, 130, 130, 75, 75, 60, 165, 167, 109, 130, 130, 31, 31, 134, 232, 185, 27, 128, 128, 176, 176, 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183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 8, 8, 112, 103, 121, 54, 145, 145, 8, 8, 112, 103, 121, 54, 145, 145, 22, 22, 72, 93, 228, 22, 185, 185, 50, 50, 141, 98, 115, 185, 99, 99, 33, 33, 33, 23, 208, 158, 234, 234, 170, 170, 10, 162, 191, 178, 124, 124, 170, 170, 10, 162, 191, 178, 124, 124, 33, 33, 33, 23, 208, 158, 234, 234, 50, 50, 141, 98, 115, 185, 99, 99, 22, 22, 72, 93, 228, 22, 185, 185, 8, 8, 112, 103, 121, 54, 145, 145, 129, 129, 115, 78, 158, 55, 222, 222, 129, 129, 115, 78, 158, 55, 222, 222, 235, 235, 179, 108, 127, 143, 16, 16, 104, 104, 130, 47, 27, 197, 92, 92, 129, 129, 225, 151, 73, 240, 93, 93, 9, 9, 168, 28, 77, 206, 165, 165, 9, 9, 168, 28, 77, 206, 165, 165, 129, 129, 225, 151, 73, 240, 93, 93, 104, 104, 130, 47, 27, 197, 92, 92, 235, 235, 179, 108, 127, 143, 16, 16, 129, 129, 115, 78, 158, 55, 222, 222, 38, 38, 18, 12, 43, 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165, 78, 149, 150, 143, 42, 42, 233, 233, 231, 18, 24, 205, 181, 181, 233, 233, 231, 18, 24, 205, 181, 181, 233, 233, 231, 18, 24, 205, 181, 181, 165, 165, 78, 149, 150, 143, 42, 42, 107, 107, 98, 178, 243, 232, 135, 135, 111, 111, 68, 13, 11, 116, 80, 80, 95, 95, 218, 130, 139, 61, 10, 10, 95, 95, 218, 130, 139, 61, 10, 10, 111, 111, 68, 13, 11, 116, 80, 80, 107, 107, 98, 178, 243, 232, 135, 135, 165, 165, 78, 149, 150, 143, 42, 42, 233, 233, 231, 18, 24, 205, 181, 181, 82, 82, 37, 126, 244, 166, 48, 48, 82, 82, 37, 126, 244, 166, 48, 48, 218, 218, 195, 180, 222, 187, 194, 194, 89, 89, 239, 235, 43, 185, 176, 176, 115, 115, 131, 122, 226, 124, 204, 204, 89, 89, 216, 220, 115, 140, 225, 225, 89, 89, 216, 220, 115, 140, 225, 225, 115, 115, 131, 122, 226, 124, 204, 204, 89, 89, 239, 235, 43, 185, 176, 176, 218, 218, 195, 180, 222, 187, 194, 194, 82, 82, 37, 126, 244, 166, 48, 48, 178, 178, 121, 57, 82, 172, 44, 44, 178, 178, 121, 57, 82, 172, 44, 44, 222, 222, 68, 223, 78, 234, 173, 173, 125, 125, 128, 160, 145, 79, 54, 54, 127, 127, 228, 154, 22, 201, 178, 178, 222, 222, 50, 183, 18, 161, 70, 70, 222, 222, 50, 183, 18, 161, 70, 70, 127, 127, 228, 154, 22, 201, 178, 178, 125, 125, 128, 160, 145, 79, 54, 54, 222, 222, 68, 223, 78, 234, 173, 173, 178, 178, 121, 57, 82, 172, 44, 44, 58, 58, 214, 30, 129, 209, 63, 63, 58, 58, 214, 30, 129, 209, 63, 63, 55, 55, 215, 106, 176, 12, 91, 91, 45, 45, 165, 24, 233, 10, 179, 179, 9, 9, 65, 199, 42, 48, 170, 170, 97, 97, 14, 242, 40, 13, 87, 87, 97, 97, 14, 242, 40, 13, 87, 87, 9, 9, 65, 199, 42, 48, 170, 170, 45, 45, 165, 24, 233, 10, 179, 179, 55, 55, 215, 106, 176, 12, 91, 91, 58, 58, 214, 30, 129, 209, 63, 63, 58, 58, 214, 30, 129, 209, 63, 63, 58, 58, 214, 30, 129, 209, 63, 63, 55, 55, 215, 106, 176, 12, 91, 91, 45, 45, 165, 24, 233, 10, 179, 179, 9, 9, 65, 199, 42, 48, 170, 170, 97, 97, 14, 242, 40, 13, 87, 87, 97, 97, 14, 242, 40, 13, 87, 87, 9, 9, 65, 199, 42, 48, 170, 170, 45, 45, 165, 24, 233, 10, 179, 179, 55, 55, 215, 106, 176, 12, 91, 91, 58, 58, 214, 30, 129, 209, 63, 63, 178, 178, 121, 57, 82, 172, 44, 44, 178, 178, 121, 57, 82, 172, 44, 44, 222, 222, 68, 223, 78, 234, 173, 173, 125, 125, 128, 160, 145, 79, 54, 54, 127, 127, 228, 154, 22, 201, 178, 178, 222, 222, 50, 183, 18, 161, 70, 70, 222, 222, 50, 183, 18, 161, 70, 70, 127, 127, 228, 154, 22, 201, 178, 178, 125, 125, 128, 160, 145, 79, 54, 54, 222, 222, 68, 223, 78, 234, 173, 173, 178, 178, 121, 57, 82, 172, 44, 44}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // in4_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({233, 231, 18, 24, 205, 181, 165, 78, 149, 150, 143, 42, 107, 98, 178, 243, 232, 135, 111, 68, 13, 11, 116, 80, 95, 218, 130, 139, 61, 10, 82, 37, 126, 244, 166, 48, 218, 195, 180, 222, 187, 194, 89, 239, 235, 43, 185, 176, 115, 131, 122, 226, 124, 204, 89, 216, 220, 115, 140, 225, 178, 121, 57, 82, 172, 44, 222, 68, 223, 78, 234, 173, 125, 128, 160, 145, 79, 54, 127, 228, 154, 22, 201, 178, 222, 50, 183, 18, 161, 70, 58, 214, 30, 129, 209, 63, 55, 215, 106, 176, 12, 91, 45, 165, 24, 233, 10, 179, 9, 65, 199, 42, 48, 170, 97, 14, 242, 40, 13, 87, 152, 182, 31, 85, 11, 112, 188, 182, 220, 185, 211, 173, 117, 58, 163, 80, 28, 111, 214, 35, 144, 98, 128, 39, 234, 66, 149, 105, 8, 138, 38, 18, 12, 43, 27, 156, 126, 240, 228, 243, 60, 111, 64, 146, 154, 196, 174, 66, 106, 130, 5, 13, 102, 31, 178, 62, 28, 48, 60, 56, 129, 115, 78, 158, 55, 222, 235, 179, 108, 127, 143, 16, 104, 130, 47, 27, 197, 92, 129, 225, 151, 73, 240, 93, 9, 168, 28, 77, 206, 165, 8, 112, 103, 121, 54, 145, 22, 72, 93, 228, 22, 185, 50, 141, 98, 115, 185, 99, 33, 33, 23, 208, 158, 234, 170, 10, 162, 191, 178, 124, 90, 114, 196, 69, 130, 119, 233, 197, 228, 205, 75, 60, 121, 66, 107, 167, 224, 145, 200, 27, 89, 243, 39, 104, 20, 25, 219, 241, 160, 35, 75, 60, 165, 167, 109, 130, 31, 134, 232, 185, 27, 128, 176, 66, 219, 115, 173, 101, 243, 192, 142, 39, 110, 11, 147, 216, 47, 126, 120, 101, 175, 229, 173, 117, 235, 83, 183, 162, 187, 208, 58, 153, 101, 164, 239, 156, 7, 115, 175, 216, 160, 200, 8, 230, 179, 150, 221, 216, 28, 200, 188, 52, 183, 145, 50, 197, 37, 151, 108, 65, 140, 116, 53, 236, 21, 5, 121, 205, 162, 185, 120, 166, 84, 68, 125, 11, 23, 185, 46, 184}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // placeholder20
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({4}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // param25
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_quant8_asymm_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_three_symmetric_quant8_asymm_all_inputs_as_internal", get_test_model_three_symmetric_quant8_asymm_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_quant8_asymm_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({233, 231, 18, 24, 205, 181, 165, 78, 149, 150, 143, 42, 107, 98, 178, 243, 232, 135, 111, 68, 13, 11, 116, 80, 95, 218, 130, 139, 61, 10, 82, 37, 126, 244, 166, 48, 218, 195, 180, 222, 187, 194, 89, 239, 235, 43, 185, 176, 115, 131, 122, 226, 124, 204, 89, 216, 220, 115, 140, 225, 178, 121, 57, 82, 172, 44, 222, 68, 223, 78, 234, 173, 125, 128, 160, 145, 79, 54, 127, 228, 154, 22, 201, 178, 222, 50, 183, 18, 161, 70, 58, 214, 30, 129, 209, 63, 55, 215, 106, 176, 12, 91, 45, 165, 24, 233, 10, 179, 9, 65, 199, 42, 48, 170, 97, 14, 242, 40, 13, 87, 152, 182, 31, 85, 11, 112, 188, 182, 220, 185, 211, 173, 117, 58, 163, 80, 28, 111, 214, 35, 144, 98, 128, 39, 234, 66, 149, 105, 8, 138, 38, 18, 12, 43, 27, 156, 126, 240, 228, 243, 60, 111, 64, 146, 154, 196, 174, 66, 106, 130, 5, 13, 102, 31, 178, 62, 28, 48, 60, 56, 129, 115, 78, 158, 55, 222, 235, 179, 108, 127, 143, 16, 104, 130, 47, 27, 197, 92, 129, 225, 151, 73, 240, 93, 9, 168, 28, 77, 206, 165, 8, 112, 103, 121, 54, 145, 22, 72, 93, 228, 22, 185, 50, 141, 98, 115, 185, 99, 33, 33, 23, 208, 158, 234, 170, 10, 162, 191, 178, 124, 90, 114, 196, 69, 130, 119, 233, 197, 228, 205, 75, 60, 121, 66, 107, 167, 224, 145, 200, 27, 89, 243, 39, 104, 20, 25, 219, 241, 160, 35, 75, 60, 165, 167, 109, 130, 31, 134, 232, 185, 27, 128, 176, 66, 219, 115, 173, 101, 243, 192, 142, 39, 110, 11, 147, 216, 47, 126, 120, 101, 175, 229, 173, 117, 235, 83, 183, 162, 187, 208, 58, 153, 101, 164, 239, 156, 7, 115, 175, 216, 160, 200, 8, 230, 179, 150, 221, 216, 28, 200, 188, 52, 183, 145, 50, 197, 37, 151, 108, 65, 140, 116, 53, 236, 21, 5, 121, 205, 162, 185, 120, 166, 84, 68, 125, 11, 23, 185, 46, 184}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 75, 75, 60, 165, 167, 109, 130, 130, 75, 75, 60, 165, 167, 109, 130, 130, 31, 31, 134, 232, 185, 27, 128, 128, 176, 176, 66, 219, 115, 173, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 147, 147, 216, 47, 126, 120, 101, 101, 147, 147, 216, 47, 126, 120, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 176, 176, 66, 219, 115, 173, 101, 101, 31, 31, 134, 232, 185, 27, 128, 128, 75, 75, 60, 165, 167, 109, 130, 130, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 233, 233, 197, 228, 205, 75, 60, 60, 121, 121, 66, 107, 167, 224, 145, 145, 200, 200, 27, 89, 243, 39, 104, 104, 20, 20, 25, 219, 241, 160, 35, 35, 20, 20, 25, 219, 241, 160, 35, 35, 200, 200, 27, 89, 243, 39, 104, 104, 121, 121, 66, 107, 167, 224, 145, 145, 233, 233, 197, 228, 205, 75, 60, 60, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 233, 233, 197, 228, 205, 75, 60, 60, 121, 121, 66, 107, 167, 224, 145, 145, 200, 200, 27, 89, 243, 39, 104, 104, 20, 20, 25, 219, 241, 160, 35, 35, 20, 20, 25, 219, 241, 160, 35, 35, 200, 200, 27, 89, 243, 39, 104, 104, 121, 121, 66, 107, 167, 224, 145, 145, 233, 233, 197, 228, 205, 75, 60, 60, 90, 90, 114, 196, 69, 130, 119, 119, 75, 75, 60, 165, 167, 109, 130, 130, 75, 75, 60, 165, 167, 109, 130, 130, 31, 31, 134, 232, 185, 27, 128, 128, 176, 176, 66, 219, 115, 173, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 147, 147, 216, 47, 126, 120, 101, 101, 147, 147, 216, 47, 126, 120, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 176, 176, 66, 219, 115, 173, 101, 101, 31, 31, 134, 232, 185, 27, 128, 128, 75, 75, 60, 165, 167, 109, 130, 130, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 8, 8, 112, 103, 121, 54, 145, 145, 8, 8, 112, 103, 121, 54, 145, 145, 22, 22, 72, 93, 228, 22, 185, 185, 50, 50, 141, 98, 115, 185, 99, 99, 33, 33, 33, 23, 208, 158, 234, 234, 170, 170, 10, 162, 191, 178, 124, 124, 170, 170, 10, 162, 191, 178, 124, 124, 33, 33, 33, 23, 208, 158, 234, 234, 50, 50, 141, 98, 115, 185, 99, 99, 22, 22, 72, 93, 228, 22, 185, 185, 8, 8, 112, 103, 121, 54, 145, 145, 129, 129, 115, 78, 158, 55, 222, 222, 129, 129, 115, 78, 158, 55, 222, 222, 235, 235, 179, 108, 127, 143, 16, 16, 104, 104, 130, 47, 27, 197, 92, 92, 129, 129, 225, 151, 73, 240, 93, 93, 9, 9, 168, 28, 77, 206, 165, 165, 9, 9, 168, 28, 77, 206, 165, 165, 129, 129, 225, 151, 73, 240, 93, 93, 104, 104, 130, 47, 27, 197, 92, 92, 235, 235, 179, 108, 127, 143, 16, 16, 129, 129, 115, 78, 158, 55, 222, 222, 38, 38, 18, 12, 43, 27, 156, 156, 38, 38, 18, 12, 43, 27, 156, 156, 126, 126, 240, 228, 243, 60, 111, 111, 64, 64, 146, 154, 196, 174, 66, 66, 106, 106, 130, 5, 13, 102, 31, 31, 178, 178, 62, 28, 48, 60, 56, 56, 178, 178, 62, 28, 48, 60, 56, 56, 106, 106, 130, 5, 13, 102, 31, 31, 64, 64, 146, 154, 196, 174, 66, 66, 126, 126, 240, 228, 243, 60, 111, 111, 38, 38, 18, 12, 43, 27, 156, 156, 152, 152, 182, 31, 85, 11, 112, 112, 152, 152, 182, 31, 85, 11, 112, 112, 188, 188, 182, 220, 185, 211, 173, 173, 117, 117, 58, 163, 80, 28, 111, 111, 214, 214, 35, 144, 98, 128, 39, 39, 234, 234, 66, 149, 105, 8, 138, 138, 234, 234, 66, 149, 105, 8, 138, 138, 214, 214, 35, 144, 98, 128, 39, 39, 117, 117, 58, 163, 80, 28, 111, 111, 188, 188, 182, 220, 185, 211, 173, 173, 152, 152, 182, 31, 85, 11, 112, 112, 152, 152, 182, 31, 85, 11, 112, 112, 152, 152, 182, 31, 85, 11, 112, 112, 188, 188, 182, 220, 185, 211, 173, 173, 117, 117, 58, 163, 80, 28, 111, 111, 214, 214, 35, 144, 98, 128, 39, 39, 234, 234, 66, 149, 105, 8, 138, 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208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 75, 75, 60, 165, 167, 109, 130, 130, 75, 75, 60, 165, 167, 109, 130, 130, 31, 31, 134, 232, 185, 27, 128, 128, 176, 176, 66, 219, 115, 173, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 147, 147, 216, 47, 126, 120, 101, 101, 147, 147, 216, 47, 126, 120, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 176, 176, 66, 219, 115, 173, 101, 101, 31, 31, 134, 232, 185, 27, 128, 128, 75, 75, 60, 165, 167, 109, 130, 130, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 233, 233, 197, 228, 205, 75, 60, 60, 121, 121, 66, 107, 167, 224, 145, 145, 200, 200, 27, 89, 243, 39, 104, 104, 20, 20, 25, 219, 241, 160, 35, 35, 20, 20, 25, 219, 241, 160, 35, 35, 200, 200, 27, 89, 243, 39, 104, 104, 121, 121, 66, 107, 167, 224, 145, 145, 233, 233, 197, 228, 205, 75, 60, 60, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 233, 233, 197, 228, 205, 75, 60, 60, 121, 121, 66, 107, 167, 224, 145, 145, 200, 200, 27, 89, 243, 39, 104, 104, 20, 20, 25, 219, 241, 160, 35, 35, 20, 20, 25, 219, 241, 160, 35, 35, 200, 200, 27, 89, 243, 39, 104, 104, 121, 121, 66, 107, 167, 224, 145, 145, 233, 233, 197, 228, 205, 75, 60, 60, 90, 90, 114, 196, 69, 130, 119, 119, 75, 75, 60, 165, 167, 109, 130, 130, 75, 75, 60, 165, 167, 109, 130, 130, 31, 31, 134, 232, 185, 27, 128, 128, 176, 176, 66, 219, 115, 173, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 147, 147, 216, 47, 126, 120, 101, 101, 147, 147, 216, 47, 126, 120, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 176, 176, 66, 219, 115, 173, 101, 101, 31, 31, 134, 232, 185, 27, 128, 128, 75, 75, 60, 165, 167, 109, 130, 130, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 8, 8, 112, 103, 121, 54, 145, 145, 8, 8, 112, 103, 121, 54, 145, 145, 22, 22, 72, 93, 228, 22, 185, 185, 50, 50, 141, 98, 115, 185, 99, 99, 33, 33, 33, 23, 208, 158, 234, 234, 170, 170, 10, 162, 191, 178, 124, 124, 170, 170, 10, 162, 191, 178, 124, 124, 33, 33, 33, 23, 208, 158, 234, 234, 50, 50, 141, 98, 115, 185, 99, 99, 22, 22, 72, 93, 228, 22, 185, 185, 8, 8, 112, 103, 121, 54, 145, 145, 129, 129, 115, 78, 158, 55, 222, 222, 129, 129, 115, 78, 158, 55, 222, 222, 235, 235, 179, 108, 127, 143, 16, 16, 104, 104, 130, 47, 27, 197, 92, 92, 129, 129, 225, 151, 73, 240, 93, 93, 9, 9, 168, 28, 77, 206, 165, 165, 9, 9, 168, 28, 77, 206, 165, 165, 129, 129, 225, 151, 73, 240, 93, 93, 104, 104, 130, 47, 27, 197, 92, 92, 235, 235, 179, 108, 127, 143, 16, 16, 129, 129, 115, 78, 158, 55, 222, 222, 38, 38, 18, 12, 43, 27, 156, 156, 38, 38, 18, 12, 43, 27, 156, 156, 126, 126, 240, 228, 243, 60, 111, 111, 64, 64, 146, 154, 196, 174, 66, 66, 106, 106, 130, 5, 13, 102, 31, 31, 178, 178, 62, 28, 48, 60, 56, 56, 178, 178, 62, 28, 48, 60, 56, 56, 106, 106, 130, 5, 13, 102, 31, 31, 64, 64, 146, 154, 196, 174, 66, 66, 126, 126, 240, 228, 243, 60, 111, 111, 38, 38, 18, 12, 43, 27, 156, 156, 152, 152, 182, 31, 85, 11, 112, 112, 152, 152, 182, 31, 85, 11, 112, 112, 188, 188, 182, 220, 185, 211, 173, 173, 117, 117, 58, 163, 80, 28, 111, 111, 214, 214, 35, 144, 98, 128, 39, 39, 234, 234, 66, 149, 105, 8, 138, 138, 234, 234, 66, 149, 105, 8, 138, 138, 214, 214, 35, 144, 98, 128, 39, 39, 117, 117, 58, 163, 80, 28, 111, 111, 188, 188, 182, 220, 185, 211, 173, 173, 152, 152, 182, 31, 85, 11, 112, 112, 152, 152, 182, 31, 85, 11, 112, 112, 152, 152, 182, 31, 85, 11, 112, 112, 188, 188, 182, 220, 185, 211, 173, 173, 117, 117, 58, 163, 80, 28, 111, 111, 214, 214, 35, 144, 98, 128, 39, 39, 234, 234, 66, 149, 105, 8, 138, 138, 234, 234, 66, 149, 105, 8, 138, 138, 214, 214, 35, 144, 98, 128, 39, 39, 117, 117, 58, 163, 80, 28, 111, 111, 188, 188, 182, 220, 185, 211, 173, 173, 152, 152, 182, 31, 85, 11, 112, 112, 38, 38, 18, 12, 43, 27, 156, 156, 38, 38, 18, 12, 43, 27, 156, 156, 126, 126, 240, 228, 243, 60, 111, 111, 64, 64, 146, 154, 196, 174, 66, 66, 106, 106, 130, 5, 13, 102, 31, 31, 178, 178, 62, 28, 48, 60, 56, 56, 178, 178, 62, 28, 48, 60, 56, 56, 106, 106, 130, 5, 13, 102, 31, 31, 64, 64, 146, 154, 196, 174, 66, 66, 126, 126, 240, 228, 243, 60, 111, 111, 38, 38, 18, 12, 43, 27, 156, 156, 129, 129, 115, 78, 158, 55, 222, 222, 129, 129, 115, 78, 158, 55, 222, 222, 235, 235, 179, 108, 127, 143, 16, 16, 104, 104, 130, 47, 27, 197, 92, 92, 129, 129, 225, 151, 73, 240, 93, 93, 9, 9, 168, 28, 77, 206, 165, 165, 9, 9, 168, 28, 77, 206, 165, 165, 129, 129, 225, 151, 73, 240, 93, 93, 104, 104, 130, 47, 27, 197, 92, 92, 235, 235, 179, 108, 127, 143, 16, 16, 129, 129, 115, 78, 158, 55, 222, 222, 8, 8, 112, 103, 121, 54, 145, 145, 8, 8, 112, 103, 121, 54, 145, 145, 22, 22, 72, 93, 228, 22, 185, 185, 50, 50, 141, 98, 115, 185, 99, 99, 33, 33, 33, 23, 208, 158, 234, 234, 170, 170, 10, 162, 191, 178, 124, 124, 170, 170, 10, 162, 191, 178, 124, 124, 33, 33, 33, 23, 208, 158, 234, 234, 50, 50, 141, 98, 115, 185, 99, 99, 22, 22, 72, 93, 228, 22, 185, 185, 8, 8, 112, 103, 121, 54, 145, 145, 8, 8, 112, 103, 121, 54, 145, 145, 8, 8, 112, 103, 121, 54, 145, 145, 22, 22, 72, 93, 228, 22, 185, 185, 50, 50, 141, 98, 115, 185, 99, 99, 33, 33, 33, 23, 208, 158, 234, 234, 170, 170, 10, 162, 191, 178, 124, 124, 170, 170, 10, 162, 191, 178, 124, 124, 33, 33, 33, 23, 208, 158, 234, 234, 50, 50, 141, 98, 115, 185, 99, 99, 22, 22, 72, 93, 228, 22, 185, 185, 8, 8, 112, 103, 121, 54, 145, 145, 129, 129, 115, 78, 158, 55, 222, 222, 129, 129, 115, 78, 158, 55, 222, 222, 235, 235, 179, 108, 127, 143, 16, 16, 104, 104, 130, 47, 27, 197, 92, 92, 129, 129, 225, 151, 73, 240, 93, 93, 9, 9, 168, 28, 77, 206, 165, 165, 9, 9, 168, 28, 77, 206, 165, 165, 129, 129, 225, 151, 73, 240, 93, 93, 104, 104, 130, 47, 27, 197, 92, 92, 235, 235, 179, 108, 127, 143, 16, 16, 129, 129, 115, 78, 158, 55, 222, 222, 58, 58, 214, 30, 129, 209, 63, 63, 58, 58, 214, 30, 129, 209, 63, 63, 55, 55, 215, 106, 176, 12, 91, 91, 45, 45, 165, 24, 233, 10, 179, 179, 9, 9, 65, 199, 42, 48, 170, 170, 97, 97, 14, 242, 40, 13, 87, 87, 97, 97, 14, 242, 40, 13, 87, 87, 9, 9, 65, 199, 42, 48, 170, 170, 45, 45, 165, 24, 233, 10, 179, 179, 55, 55, 215, 106, 176, 12, 91, 91, 58, 58, 214, 30, 129, 209, 63, 63, 178, 178, 121, 57, 82, 172, 44, 44, 178, 178, 121, 57, 82, 172, 44, 44, 222, 222, 68, 223, 78, 234, 173, 173, 125, 125, 128, 160, 145, 79, 54, 54, 127, 127, 228, 154, 22, 201, 178, 178, 222, 222, 50, 183, 18, 161, 70, 70, 222, 222, 50, 183, 18, 161, 70, 70, 127, 127, 228, 154, 22, 201, 178, 178, 125, 125, 128, 160, 145, 79, 54, 54, 222, 222, 68, 223, 78, 234, 173, 173, 178, 178, 121, 57, 82, 172, 44, 44, 82, 82, 37, 126, 244, 166, 48, 48, 82, 82, 37, 126, 244, 166, 48, 48, 218, 218, 195, 180, 222, 187, 194, 194, 89, 89, 239, 235, 43, 185, 176, 176, 115, 115, 131, 122, 226, 124, 204, 204, 89, 89, 216, 220, 115, 140, 225, 225, 89, 89, 216, 220, 115, 140, 225, 225, 115, 115, 131, 122, 226, 124, 204, 204, 89, 89, 239, 235, 43, 185, 176, 176, 218, 218, 195, 180, 222, 187, 194, 194, 82, 82, 37, 126, 244, 166, 48, 48, 233, 233, 231, 18, 24, 205, 181, 181, 233, 233, 231, 18, 24, 205, 181, 181, 165, 165, 78, 149, 150, 143, 42, 42, 107, 107, 98, 178, 243, 232, 135, 135, 111, 111, 68, 13, 11, 116, 80, 80, 95, 95, 218, 130, 139, 61, 10, 10, 95, 95, 218, 130, 139, 61, 10, 10, 111, 111, 68, 13, 11, 116, 80, 80, 107, 107, 98, 178, 243, 232, 135, 135, 165, 165, 78, 149, 150, 143, 42, 42, 233, 233, 231, 18, 24, 205, 181, 181, 233, 233, 231, 18, 24, 205, 181, 181, 233, 233, 231, 18, 24, 205, 181, 181, 165, 165, 78, 149, 150, 143, 42, 42, 107, 107, 98, 178, 243, 232, 135, 135, 111, 111, 68, 13, 11, 116, 80, 80, 95, 95, 218, 130, 139, 61, 10, 10, 95, 95, 218, 130, 139, 61, 10, 10, 111, 111, 68, 13, 11, 116, 80, 80, 107, 107, 98, 178, 243, 232, 135, 135, 165, 165, 78, 149, 150, 143, 42, 42, 233, 233, 231, 18, 24, 205, 181, 181, 82, 82, 37, 126, 244, 166, 48, 48, 82, 82, 37, 126, 244, 166, 48, 48, 218, 218, 195, 180, 222, 187, 194, 194, 89, 89, 239, 235, 43, 185, 176, 176, 115, 115, 131, 122, 226, 124, 204, 204, 89, 89, 216, 220, 115, 140, 225, 225, 89, 89, 216, 220, 115, 140, 225, 225, 115, 115, 131, 122, 226, 124, 204, 204, 89, 89, 239, 235, 43, 185, 176, 176, 218, 218, 195, 180, 222, 187, 194, 194, 82, 82, 37, 126, 244, 166, 48, 48, 178, 178, 121, 57, 82, 172, 44, 44, 178, 178, 121, 57, 82, 172, 44, 44, 222, 222, 68, 223, 78, 234, 173, 173, 125, 125, 128, 160, 145, 79, 54, 54, 127, 127, 228, 154, 22, 201, 178, 178, 222, 222, 50, 183, 18, 161, 70, 70, 222, 222, 50, 183, 18, 161, 70, 70, 127, 127, 228, 154, 22, 201, 178, 178, 125, 125, 128, 160, 145, 79, 54, 54, 222, 222, 68, 223, 78, 234, 173, 173, 178, 178, 121, 57, 82, 172, 44, 44, 58, 58, 214, 30, 129, 209, 63, 63, 58, 58, 214, 30, 129, 209, 63, 63, 55, 55, 215, 106, 176, 12, 91, 91, 45, 45, 165, 24, 233, 10, 179, 179, 9, 9, 65, 199, 42, 48, 170, 170, 97, 97, 14, 242, 40, 13, 87, 87, 97, 97, 14, 242, 40, 13, 87, 87, 9, 9, 65, 199, 42, 48, 170, 170, 45, 45, 165, 24, 233, 10, 179, 179, 55, 55, 215, 106, 176, 12, 91, 91, 58, 58, 214, 30, 129, 209, 63, 63, 58, 58, 214, 30, 129, 209, 63, 63, 58, 58, 214, 30, 129, 209, 63, 63, 55, 55, 215, 106, 176, 12, 91, 91, 45, 45, 165, 24, 233, 10, 179, 179, 9, 9, 65, 199, 42, 48, 170, 170, 97, 97, 14, 242, 40, 13, 87, 87, 97, 97, 14, 242, 40, 13, 87, 87, 9, 9, 65, 199, 42, 48, 170, 170, 45, 45, 165, 24, 233, 10, 179, 179, 55, 55, 215, 106, 176, 12, 91, 91, 58, 58, 214, 30, 129, 209, 63, 63, 178, 178, 121, 57, 82, 172, 44, 44, 178, 178, 121, 57, 82, 172, 44, 44, 222, 222, 68, 223, 78, 234, 173, 173, 125, 125, 128, 160, 145, 79, 54, 54, 127, 127, 228, 154, 22, 201, 178, 178, 222, 222, 50, 183, 18, 161, 70, 70, 222, 222, 50, 183, 18, 161, 70, 70, 127, 127, 228, 154, 22, 201, 178, 178, 125, 125, 128, 160, 145, 79, 54, 54, 222, 222, 68, 223, 78, 234, 173, 173, 178, 178, 121, 57, 82, 172, 44, 44}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_quant8_asymm_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_three_symmetric_quant8_asymm_all_tensors_as_inputs", get_test_model_three_symmetric_quant8_asymm_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({188, 188, 52, 183, 145, 50, 197, 197, 188, 188, 52, 183, 145, 50, 197, 197, 37, 37, 151, 108, 65, 140, 116, 116, 53, 53, 236, 21, 5, 121, 205, 205, 162, 162, 185, 120, 166, 84, 68, 68, 125, 125, 11, 23, 185, 46, 184, 184, 125, 125, 11, 23, 185, 46, 184, 184, 162, 162, 185, 120, 166, 84, 68, 68, 53, 53, 236, 21, 5, 121, 205, 205, 37, 37, 151, 108, 65, 140, 116, 116, 188, 188, 52, 183, 145, 50, 197, 197, 175, 175, 229, 173, 117, 235, 83, 83, 175, 175, 229, 173, 117, 235, 83, 83, 183, 183, 162, 187, 208, 58, 153, 153, 101, 101, 164, 239, 156, 7, 115, 115, 175, 175, 216, 160, 200, 8, 230, 230, 179, 179, 150, 221, 216, 28, 200, 200, 179, 179, 150, 221, 216, 28, 200, 200, 175, 175, 216, 160, 200, 8, 230, 230, 101, 101, 164, 239, 156, 7, 115, 115, 183, 183, 162, 187, 208, 58, 153, 153, 175, 175, 229, 173, 117, 235, 83, 83, 75, 75, 60, 165, 167, 109, 130, 130, 75, 75, 60, 165, 167, 109, 130, 130, 31, 31, 134, 232, 185, 27, 128, 128, 176, 176, 66, 219, 115, 173, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 147, 147, 216, 47, 126, 120, 101, 101, 147, 147, 216, 47, 126, 120, 101, 101, 243, 243, 192, 142, 39, 110, 11, 11, 176, 176, 66, 219, 115, 173, 101, 101, 31, 31, 134, 232, 185, 27, 128, 128, 75, 75, 60, 165, 167, 109, 130, 130, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 233, 233, 197, 228, 205, 75, 60, 60, 121, 121, 66, 107, 167, 224, 145, 145, 200, 200, 27, 89, 243, 39, 104, 104, 20, 20, 25, 219, 241, 160, 35, 35, 20, 20, 25, 219, 241, 160, 35, 35, 200, 200, 27, 89, 243, 39, 104, 104, 121, 121, 66, 107, 167, 224, 145, 145, 233, 233, 197, 228, 205, 75, 60, 60, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 90, 90, 114, 196, 69, 130, 119, 119, 233, 233, 197, 228, 205, 75, 60, 60, 121, 121, 66, 107, 167, 224, 145, 145, 200, 200, 27, 89, 243, 39, 104, 104, 20, 20, 25, 219, 241, 160, 35, 35, 20, 20, 25, 219, 241, 160, 35, 35, 200, 200, 27, 89, 243, 39, 104, 104, 121, 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165, 78, 149, 150, 143, 42, 42, 233, 233, 231, 18, 24, 205, 181, 181, 233, 233, 231, 18, 24, 205, 181, 181, 233, 233, 231, 18, 24, 205, 181, 181, 165, 165, 78, 149, 150, 143, 42, 42, 107, 107, 98, 178, 243, 232, 135, 135, 111, 111, 68, 13, 11, 116, 80, 80, 95, 95, 218, 130, 139, 61, 10, 10, 95, 95, 218, 130, 139, 61, 10, 10, 111, 111, 68, 13, 11, 116, 80, 80, 107, 107, 98, 178, 243, 232, 135, 135, 165, 165, 78, 149, 150, 143, 42, 42, 233, 233, 231, 18, 24, 205, 181, 181, 82, 82, 37, 126, 244, 166, 48, 48, 82, 82, 37, 126, 244, 166, 48, 48, 218, 218, 195, 180, 222, 187, 194, 194, 89, 89, 239, 235, 43, 185, 176, 176, 115, 115, 131, 122, 226, 124, 204, 204, 89, 89, 216, 220, 115, 140, 225, 225, 89, 89, 216, 220, 115, 140, 225, 225, 115, 115, 131, 122, 226, 124, 204, 204, 89, 89, 239, 235, 43, 185, 176, 176, 218, 218, 195, 180, 222, 187, 194, 194, 82, 82, 37, 126, 244, 166, 48, 48, 178, 178, 121, 57, 82, 172, 44, 44, 178, 178, 121, 57, 82, 172, 44, 44, 222, 222, 68, 223, 78, 234, 173, 173, 125, 125, 128, 160, 145, 79, 54, 54, 127, 127, 228, 154, 22, 201, 178, 178, 222, 222, 50, 183, 18, 161, 70, 70, 222, 222, 50, 183, 18, 161, 70, 70, 127, 127, 228, 154, 22, 201, 178, 178, 125, 125, 128, 160, 145, 79, 54, 54, 222, 222, 68, 223, 78, 234, 173, 173, 178, 178, 121, 57, 82, 172, 44, 44, 58, 58, 214, 30, 129, 209, 63, 63, 58, 58, 214, 30, 129, 209, 63, 63, 55, 55, 215, 106, 176, 12, 91, 91, 45, 45, 165, 24, 233, 10, 179, 179, 9, 9, 65, 199, 42, 48, 170, 170, 97, 97, 14, 242, 40, 13, 87, 87, 97, 97, 14, 242, 40, 13, 87, 87, 9, 9, 65, 199, 42, 48, 170, 170, 45, 45, 165, 24, 233, 10, 179, 179, 55, 55, 215, 106, 176, 12, 91, 91, 58, 58, 214, 30, 129, 209, 63, 63, 58, 58, 214, 30, 129, 209, 63, 63, 58, 58, 214, 30, 129, 209, 63, 63, 55, 55, 215, 106, 176, 12, 91, 91, 45, 45, 165, 24, 233, 10, 179, 179, 9, 9, 65, 199, 42, 48, 170, 170, 97, 97, 14, 242, 40, 13, 87, 87, 97, 97, 14, 242, 40, 13, 87, 87, 9, 9, 65, 199, 42, 48, 170, 170, 45, 45, 165, 24, 233, 10, 179, 179, 55, 55, 215, 106, 176, 12, 91, 91, 58, 58, 214, 30, 129, 209, 63, 63, 178, 178, 121, 57, 82, 172, 44, 44, 178, 178, 121, 57, 82, 172, 44, 44, 222, 222, 68, 223, 78, 234, 173, 173, 125, 125, 128, 160, 145, 79, 54, 54, 127, 127, 228, 154, 22, 201, 178, 178, 222, 222, 50, 183, 18, 161, 70, 70, 222, 222, 50, 183, 18, 161, 70, 70, 127, 127, 228, 154, 22, 201, 178, 178, 125, 125, 128, 160, 145, 79, 54, 54, 222, 222, 68, 223, 78, 234, 173, 173, 178, 178, 121, 57, 82, 172, 44, 44}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // in4_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({233, 231, 18, 24, 205, 181, 165, 78, 149, 150, 143, 42, 107, 98, 178, 243, 232, 135, 111, 68, 13, 11, 116, 80, 95, 218, 130, 139, 61, 10, 82, 37, 126, 244, 166, 48, 218, 195, 180, 222, 187, 194, 89, 239, 235, 43, 185, 176, 115, 131, 122, 226, 124, 204, 89, 216, 220, 115, 140, 225, 178, 121, 57, 82, 172, 44, 222, 68, 223, 78, 234, 173, 125, 128, 160, 145, 79, 54, 127, 228, 154, 22, 201, 178, 222, 50, 183, 18, 161, 70, 58, 214, 30, 129, 209, 63, 55, 215, 106, 176, 12, 91, 45, 165, 24, 233, 10, 179, 9, 65, 199, 42, 48, 170, 97, 14, 242, 40, 13, 87, 152, 182, 31, 85, 11, 112, 188, 182, 220, 185, 211, 173, 117, 58, 163, 80, 28, 111, 214, 35, 144, 98, 128, 39, 234, 66, 149, 105, 8, 138, 38, 18, 12, 43, 27, 156, 126, 240, 228, 243, 60, 111, 64, 146, 154, 196, 174, 66, 106, 130, 5, 13, 102, 31, 178, 62, 28, 48, 60, 56, 129, 115, 78, 158, 55, 222, 235, 179, 108, 127, 143, 16, 104, 130, 47, 27, 197, 92, 129, 225, 151, 73, 240, 93, 9, 168, 28, 77, 206, 165, 8, 112, 103, 121, 54, 145, 22, 72, 93, 228, 22, 185, 50, 141, 98, 115, 185, 99, 33, 33, 23, 208, 158, 234, 170, 10, 162, 191, 178, 124, 90, 114, 196, 69, 130, 119, 233, 197, 228, 205, 75, 60, 121, 66, 107, 167, 224, 145, 200, 27, 89, 243, 39, 104, 20, 25, 219, 241, 160, 35, 75, 60, 165, 167, 109, 130, 31, 134, 232, 185, 27, 128, 176, 66, 219, 115, 173, 101, 243, 192, 142, 39, 110, 11, 147, 216, 47, 126, 120, 101, 175, 229, 173, 117, 235, 83, 183, 162, 187, 208, 58, 153, 101, 164, 239, 156, 7, 115, 175, 216, 160, 200, 8, 230, 179, 150, 221, 216, 28, 200, 188, 52, 183, 145, 50, 197, 37, 151, 108, 65, 140, 116, 53, 236, 21, 5, 121, 205, 162, 185, 120, 166, 84, 68, 125, 11, 23, 185, 46, 184}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // placeholder21
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({4}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.125f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // param26
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_three_symmetric_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_three_symmetric_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_quant8_asymm_signed() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({106, 105, -2, 1, 91, 79, 71, 28, 64, 64, 61, 10, 43, 38, 78, 110, 105, 56, 44, 23, -5, -6, 47, 29, 37, 98, 54, 58, 19, -6, 30, 7, 52, 111, 72, 13, 98, 87, 79, 100, 83, 86, 33, 109, 106, 10, 81, 77, 46, 55, 50, 102, 51, 91, 33, 97, 99, 46, 59, 101, 78, 49, 18, 30, 75, 11, 100, 23, 100, 28, 106, 76, 52, 53, 69, 62, 28, 16, 52, 103, 66, 0, 89, 78, 100, 14, 80, -2, 69, 24, 18, 96, 4, 54, 93, 20, 16, 97, 42, 77, -5, 34, 12, 72, 1, 106, -6, 79, -6, 22, 89, 10, 13, 74, 37, -4, 110, 9, -5, 32, 65, 80, 5, 31, -5, 45, 83, 80, 99, 82, 94, 76, 48, 18, 70, 29, 3, 45, 96, 6, 61, 38, 53, 8, 106, 22, 64, 41, -7, 58, 8, -2, -5, 10, 3, 67, 52, 109, 103, 110, 19, 44, 21, 62, 66, 87, 76, 22, 42, 54, -8, -5, 40, 4, 78, 20, 3, 13, 19, 17, 53, 47, 28, 68, 16, 100, 107, 78, 43, 52, 61, -3, 41, 54, 13, 2, 87, 35, 53, 102, 64, 26, 109, 36, -7, 73, 3, 28, 92, 72, -7, 45, 40, 49, 16, 62, 0, 25, 36, 103, 0, 82, 14, 60, 38, 47, 81, 38, 6, 6, 1, 93, 68, 106, 74, -6, 70, 84, 78, 51, 34, 46, 87, 23, 54, 48, 106, 88, 103, 91, 27, 19, 50, 22, 42, 72, 101, 61, 89, 3, 34, 111, 9, 41, -1, 1, 98, 110, 69, 6, 27, 19, 71, 73, 44, 54, 4, 56, 105, 82, 3, 53, 77, 22, 98, 46, 75, 39, 110, 85, 60, 8, 44, -5, 62, 97, 13, 52, 49, 40, 76, 103, 76, 48, 106, 31, 80, 70, 82, 93, 18, 66, 39, 71, 108, 67, -8, 47, 76, 97, 69, 89, -7, 104, 79, 64, 100, 97, 3, 89, 83, 15, 80, 61, 14, 88, 8, 64, 43, 21, 59, 47, 16, 107, 0, -9, 49, 91, 70, 82, 49, 72, 31, 23, 51, -6, 1, 81, 12, 81}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({83, 83, 15, 80, 61, 14, 88, 88, 83, 83, 15, 80, 61, 14, 88, 88, 8, 8, 64, 43, 21, 59, 47, 47, 16, 16, 107, 0, -9, 49, 91, 91, 70, 70, 82, 49, 72, 31, 23, 23, 51, 51, -6, 1, 81, 12, 81, 81, 51, 51, -6, 1, 81, 12, 81, 81, 70, 70, 82, 49, 72, 31, 23, 23, 16, 16, 107, 0, -9, 49, 91, 91, 8, 8, 64, 43, 21, 59, 47, 47, 83, 83, 15, 80, 61, 14, 88, 88, 76, 76, 103, 76, 48, 106, 31, 31, 76, 76, 103, 76, 48, 106, 31, 31, 80, 80, 70, 82, 93, 18, 66, 66, 39, 39, 71, 108, 67, -8, 47, 47, 76, 76, 97, 69, 89, -7, 104, 104, 79, 79, 64, 100, 97, 3, 89, 89, 79, 79, 64, 100, 97, 3, 89, 89, 76, 76, 97, 69, 89, -7, 104, 104, 39, 39, 71, 108, 67, -8, 47, 47, 80, 80, 70, 82, 93, 18, 66, 66, 76, 76, 103, 76, 48, 106, 31, 31, 27, 27, 19, 71, 73, 44, 54, 54, 27, 27, 19, 71, 73, 44, 54, 54, 4, 4, 56, 105, 82, 3, 53, 53, 77, 77, 22, 98, 46, 75, 39, 39, 110, 110, 85, 60, 8, 44, -5, -5, 62, 62, 97, 13, 52, 49, 40, 40, 62, 62, 97, 13, 52, 49, 40, 40, 110, 110, 85, 60, 8, 44, -5, -5, 77, 77, 22, 98, 46, 75, 39, 39, 4, 4, 56, 105, 82, 3, 53, 53, 27, 27, 19, 71, 73, 44, 54, 54, 34, 34, 46, 87, 23, 54, 48, 48, 34, 34, 46, 87, 23, 54, 48, 48, 106, 106, 88, 103, 91, 27, 19, 19, 50, 50, 22, 42, 72, 101, 61, 61, 89, 89, 3, 34, 111, 9, 41, 41, -1, -1, 1, 98, 110, 69, 6, 6, -1, -1, 1, 98, 110, 69, 6, 6, 89, 89, 3, 34, 111, 9, 41, 41, 50, 50, 22, 42, 72, 101, 61, 61, 106, 106, 88, 103, 91, 27, 19, 19, 34, 34, 46, 87, 23, 54, 48, 48, 34, 34, 46, 87, 23, 54, 48, 48, 34, 34, 46, 87, 23, 54, 48, 48, 106, 106, 88, 103, 91, 27, 19, 19, 50, 50, 22, 42, 72, 101, 61, 61, 89, 89, 3, 34, 111, 9, 41, 41, -1, -1, 1, 98, 110, 69, 6, 6, -1, -1, 1, 98, 110, 69, 6, 6, 89, 89, 3, 34, 111, 9, 41, 41, 50, 50, 22, 42, 72, 101, 61, 61, 106, 106, 88, 103, 91, 27, 19, 19, 34, 34, 46, 87, 23, 54, 48, 48, 27, 27, 19, 71, 73, 44, 54, 54, 27, 27, 19, 71, 73, 44, 54, 54, 4, 4, 56, 105, 82, 3, 53, 53, 77, 77, 22, 98, 46, 75, 39, 39, 110, 110, 85, 60, 8, 44, -5, -5, 62, 62, 97, 13, 52, 49, 40, 40, 62, 62, 97, 13, 52, 49, 40, 40, 110, 110, 85, 60, 8, 44, -5, -5, 77, 77, 22, 98, 46, 75, 39, 39, 4, 4, 56, 105, 82, 3, 53, 53, 27, 27, 19, 71, 73, 44, 54, 54, 76, 76, 103, 76, 48, 106, 31, 31, 76, 76, 103, 76, 48, 106, 31, 31, 80, 80, 70, 82, 93, 18, 66, 66, 39, 39, 71, 108, 67, -8, 47, 47, 76, 76, 97, 69, 89, -7, 104, 104, 79, 79, 64, 100, 97, 3, 89, 89, 79, 79, 64, 100, 97, 3, 89, 89, 76, 76, 97, 69, 89, -7, 104, 104, 39, 39, 71, 108, 67, -8, 47, 47, 80, 80, 70, 82, 93, 18, 66, 66, 76, 76, 103, 76, 48, 106, 31, 31, 83, 83, 15, 80, 61, 14, 88, 88, 83, 83, 15, 80, 61, 14, 88, 88, 8, 8, 64, 43, 21, 59, 47, 47, 16, 16, 107, 0, -9, 49, 91, 91, 70, 70, 82, 49, 72, 31, 23, 23, 51, 51, -6, 1, 81, 12, 81, 81, 51, 51, -6, 1, 81, 12, 81, 81, 70, 70, 82, 49, 72, 31, 23, 23, 16, 16, 107, 0, -9, 49, 91, 91, 8, 8, 64, 43, 21, 59, 47, 47, 83, 83, 15, 80, 61, 14, 88, 88, 83, 83, 15, 80, 61, 14, 88, 88, 83, 83, 15, 80, 61, 14, 88, 88, 8, 8, 64, 43, 21, 59, 47, 47, 16, 16, 107, 0, -9, 49, 91, 91, 70, 70, 82, 49, 72, 31, 23, 23, 51, 51, -6, 1, 81, 12, 81, 81, 51, 51, -6, 1, 81, 12, 81, 81, 70, 70, 82, 49, 72, 31, 23, 23, 16, 16, 107, 0, -9, 49, 91, 91, 8, 8, 64, 43, 21, 59, 47, 47, 83, 83, 15, 80, 61, 14, 88, 88, 76, 76, 103, 76, 48, 106, 31, 31, 76, 76, 103, 76, 48, 106, 31, 31, 80, 80, 70, 82, 93, 18, 66, 66, 39, 39, 71, 108, 67, -8, 47, 47, 76, 76, 97, 69, 89, -7, 104, 104, 79, 79, 64, 100, 97, 3, 89, 89, 79, 79, 64, 100, 97, 3, 89, 89, 76, 76, 97, 69, 89, -7, 104, 104, 39, 39, 71, 108, 67, -8, 47, 47, 80, 80, 70, 82, 93, 18, 66, 66, 76, 76, 103, 76, 48, 106, 31, 31, -7, -7, 45, 40, 49, 16, 62, 62, -7, -7, 45, 40, 49, 16, 62, 62, 0, 0, 25, 36, 103, 0, 82, 82, 14, 14, 60, 38, 47, 81, 38, 38, 6, 6, 6, 1, 93, 68, 106, 106, 74, 74, -6, 70, 84, 78, 51, 51, 74, 74, -6, 70, 84, 78, 51, 51, 6, 6, 6, 1, 93, 68, 106, 106, 14, 14, 60, 38, 47, 81, 38, 38, 0, 0, 25, 36, 103, 0, 82, 82, -7, -7, 45, 40, 49, 16, 62, 62, 53, 53, 47, 28, 68, 16, 100, 100, 53, 53, 47, 28, 68, 16, 100, 100, 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+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_quant8_asymm_signed = TestModelManager::get().add("mirror_pad_three_symmetric_quant8_asymm_signed", get_test_model_three_symmetric_quant8_asymm_signed());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_quant8_asymm_signed_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({83, 83, 15, 80, 61, 14, 88, 88, 83, 83, 15, 80, 61, 14, 88, 88, 8, 8, 64, 43, 21, 59, 47, 47, 16, 16, 107, 0, -9, 49, 91, 91, 70, 70, 82, 49, 72, 31, 23, 23, 51, 51, -6, 1, 81, 12, 81, 81, 51, 51, -6, 1, 81, 12, 81, 81, 70, 70, 82, 49, 72, 31, 23, 23, 16, 16, 107, 0, -9, 49, 91, 91, 8, 8, 64, 43, 21, 59, 47, 47, 83, 83, 15, 80, 61, 14, 88, 88, 76, 76, 103, 76, 48, 106, 31, 31, 76, 76, 103, 76, 48, 106, 31, 31, 80, 80, 70, 82, 93, 18, 66, 66, 39, 39, 71, 108, 67, -8, 47, 47, 76, 76, 97, 69, 89, -7, 104, 104, 79, 79, 64, 100, 97, 3, 89, 89, 79, 79, 64, 100, 97, 3, 89, 89, 76, 76, 97, 69, 89, -7, 104, 104, 39, 39, 71, 108, 67, -8, 47, 47, 80, 80, 70, 82, 93, 18, 66, 66, 76, 76, 103, 76, 48, 106, 31, 31, 27, 27, 19, 71, 73, 44, 54, 54, 27, 27, 19, 71, 73, 44, 54, 54, 4, 4, 56, 105, 82, 3, 53, 53, 77, 77, 22, 98, 46, 75, 39, 39, 110, 110, 85, 60, 8, 44, -5, -5, 62, 62, 97, 13, 52, 49, 40, 40, 62, 62, 97, 13, 52, 49, 40, 40, 110, 110, 85, 60, 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4, 54, 93, 20, 20, 16, 16, 97, 42, 77, -5, 34, 34, 12, 12, 72, 1, 106, -6, 79, 79, -6, -6, 22, 89, 10, 13, 74, 74, 37, 37, -4, 110, 9, -5, 32, 32, 37, 37, -4, 110, 9, -5, 32, 32, -6, -6, 22, 89, 10, 13, 74, 74, 12, 12, 72, 1, 106, -6, 79, 79, 16, 16, 97, 42, 77, -5, 34, 34, 18, 18, 96, 4, 54, 93, 20, 20, 78, 78, 49, 18, 30, 75, 11, 11, 78, 78, 49, 18, 30, 75, 11, 11, 100, 100, 23, 100, 28, 106, 76, 76, 52, 52, 53, 69, 62, 28, 16, 16, 52, 52, 103, 66, 0, 89, 78, 78, 100, 100, 14, 80, -2, 69, 24, 24, 100, 100, 14, 80, -2, 69, 24, 24, 52, 52, 103, 66, 0, 89, 78, 78, 52, 52, 53, 69, 62, 28, 16, 16, 100, 100, 23, 100, 28, 106, 76, 76, 78, 78, 49, 18, 30, 75, 11, 11, 18, 18, 96, 4, 54, 93, 20, 20, 18, 18, 96, 4, 54, 93, 20, 20, 16, 16, 97, 42, 77, -5, 34, 34, 12, 12, 72, 1, 106, -6, 79, 79, -6, -6, 22, 89, 10, 13, 74, 74, 37, 37, -4, 110, 9, -5, 32, 32, 37, 37, -4, 110, 9, -5, 32, 32, -6, -6, 22, 89, 10, 13, 74, 74, 12, 12, 72, 1, 106, -6, 79, 79, 16, 16, 97, 42, 77, -5, 34, 34, 18, 18, 96, 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100, 53, 53, 47, 28, 68, 16, 100, 100, 107, 107, 78, 43, 52, 61, -3, -3, 41, 41, 54, 13, 2, 87, 35, 35, 53, 53, 102, 64, 26, 109, 36, 36, -7, -7, 73, 3, 28, 92, 72, 72, -7, -7, 73, 3, 28, 92, 72, 72, 53, 53, 102, 64, 26, 109, 36, 36, 41, 41, 54, 13, 2, 87, 35, 35, 107, 107, 78, 43, 52, 61, -3, -3, 53, 53, 47, 28, 68, 16, 100, 100, 18, 18, 96, 4, 54, 93, 20, 20, 18, 18, 96, 4, 54, 93, 20, 20, 16, 16, 97, 42, 77, -5, 34, 34, 12, 12, 72, 1, 106, -6, 79, 79, -6, -6, 22, 89, 10, 13, 74, 74, 37, 37, -4, 110, 9, -5, 32, 32, 37, 37, -4, 110, 9, -5, 32, 32, -6, -6, 22, 89, 10, 13, 74, 74, 12, 12, 72, 1, 106, -6, 79, 79, 16, 16, 97, 42, 77, -5, 34, 34, 18, 18, 96, 4, 54, 93, 20, 20, 78, 78, 49, 18, 30, 75, 11, 11, 78, 78, 49, 18, 30, 75, 11, 11, 100, 100, 23, 100, 28, 106, 76, 76, 52, 52, 53, 69, 62, 28, 16, 16, 52, 52, 103, 66, 0, 89, 78, 78, 100, 100, 14, 80, -2, 69, 24, 24, 100, 100, 14, 80, -2, 69, 24, 24, 52, 52, 103, 66, 0, 89, 78, 78, 52, 52, 53, 69, 62, 28, 16, 16, 100, 100, 23, 100, 28, 106, 76, 76, 78, 78, 49, 18, 30, 75, 11, 11, 30, 30, 7, 52, 111, 72, 13, 13, 30, 30, 7, 52, 111, 72, 13, 13, 98, 98, 87, 79, 100, 83, 86, 86, 33, 33, 109, 106, 10, 81, 77, 77, 46, 46, 55, 50, 102, 51, 91, 91, 33, 33, 97, 99, 46, 59, 101, 101, 33, 33, 97, 99, 46, 59, 101, 101, 46, 46, 55, 50, 102, 51, 91, 91, 33, 33, 109, 106, 10, 81, 77, 77, 98, 98, 87, 79, 100, 83, 86, 86, 30, 30, 7, 52, 111, 72, 13, 13, 106, 106, 105, -2, 1, 91, 79, 79, 106, 106, 105, -2, 1, 91, 79, 79, 71, 71, 28, 64, 64, 61, 10, 10, 43, 43, 38, 78, 110, 105, 56, 56, 44, 44, 23, -5, -6, 47, 29, 29, 37, 37, 98, 54, 58, 19, -6, -6, 37, 37, 98, 54, 58, 19, -6, -6, 44, 44, 23, -5, -6, 47, 29, 29, 43, 43, 38, 78, 110, 105, 56, 56, 71, 71, 28, 64, 64, 61, 10, 10, 106, 106, 105, -2, 1, 91, 79, 79, 106, 106, 105, -2, 1, 91, 79, 79, 106, 106, 105, -2, 1, 91, 79, 79, 71, 71, 28, 64, 64, 61, 10, 10, 43, 43, 38, 78, 110, 105, 56, 56, 44, 44, 23, -5, -6, 47, 29, 29, 37, 37, 98, 54, 58, 19, -6, -6, 37, 37, 98, 54, 58, 19, -6, -6, 44, 44, 23, -5, -6, 47, 29, 29, 43, 43, 38, 78, 110, 105, 56, 56, 71, 71, 28, 64, 64, 61, 10, 10, 106, 106, 105, -2, 1, 91, 79, 79, 30, 30, 7, 52, 111, 72, 13, 13, 30, 30, 7, 52, 111, 72, 13, 13, 98, 98, 87, 79, 100, 83, 86, 86, 33, 33, 109, 106, 10, 81, 77, 77, 46, 46, 55, 50, 102, 51, 91, 91, 33, 33, 97, 99, 46, 59, 101, 101, 33, 33, 97, 99, 46, 59, 101, 101, 46, 46, 55, 50, 102, 51, 91, 91, 33, 33, 109, 106, 10, 81, 77, 77, 98, 98, 87, 79, 100, 83, 86, 86, 30, 30, 7, 52, 111, 72, 13, 13, 78, 78, 49, 18, 30, 75, 11, 11, 78, 78, 49, 18, 30, 75, 11, 11, 100, 100, 23, 100, 28, 106, 76, 76, 52, 52, 53, 69, 62, 28, 16, 16, 52, 52, 103, 66, 0, 89, 78, 78, 100, 100, 14, 80, -2, 69, 24, 24, 100, 100, 14, 80, -2, 69, 24, 24, 52, 52, 103, 66, 0, 89, 78, 78, 52, 52, 53, 69, 62, 28, 16, 16, 100, 100, 23, 100, 28, 106, 76, 76, 78, 78, 49, 18, 30, 75, 11, 11, 18, 18, 96, 4, 54, 93, 20, 20, 18, 18, 96, 4, 54, 93, 20, 20, 16, 16, 97, 42, 77, -5, 34, 34, 12, 12, 72, 1, 106, -6, 79, 79, -6, -6, 22, 89, 10, 13, 74, 74, 37, 37, -4, 110, 9, -5, 32, 32, 37, 37, -4, 110, 9, -5, 32, 32, -6, -6, 22, 89, 10, 13, 74, 74, 12, 12, 72, 1, 106, -6, 79, 79, 16, 16, 97, 42, 77, -5, 34, 34, 18, 18, 96, 4, 54, 93, 20, 20, 18, 18, 96, 4, 54, 93, 20, 20, 18, 18, 96, 4, 54, 93, 20, 20, 16, 16, 97, 42, 77, -5, 34, 34, 12, 12, 72, 1, 106, -6, 79, 79, -6, -6, 22, 89, 10, 13, 74, 74, 37, 37, -4, 110, 9, -5, 32, 32, 37, 37, -4, 110, 9, -5, 32, 32, -6, -6, 22, 89, 10, 13, 74, 74, 12, 12, 72, 1, 106, -6, 79, 79, 16, 16, 97, 42, 77, -5, 34, 34, 18, 18, 96, 4, 54, 93, 20, 20, 78, 78, 49, 18, 30, 75, 11, 11, 78, 78, 49, 18, 30, 75, 11, 11, 100, 100, 23, 100, 28, 106, 76, 76, 52, 52, 53, 69, 62, 28, 16, 16, 52, 52, 103, 66, 0, 89, 78, 78, 100, 100, 14, 80, -2, 69, 24, 24, 100, 100, 14, 80, -2, 69, 24, 24, 52, 52, 103, 66, 0, 89, 78, 78, 52, 52, 53, 69, 62, 28, 16, 16, 100, 100, 23, 100, 28, 106, 76, 76, 78, 78, 49, 18, 30, 75, 11, 11}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // in4_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({106, 105, -2, 1, 91, 79, 71, 28, 64, 64, 61, 10, 43, 38, 78, 110, 105, 56, 44, 23, -5, -6, 47, 29, 37, 98, 54, 58, 19, -6, 30, 7, 52, 111, 72, 13, 98, 87, 79, 100, 83, 86, 33, 109, 106, 10, 81, 77, 46, 55, 50, 102, 51, 91, 33, 97, 99, 46, 59, 101, 78, 49, 18, 30, 75, 11, 100, 23, 100, 28, 106, 76, 52, 53, 69, 62, 28, 16, 52, 103, 66, 0, 89, 78, 100, 14, 80, -2, 69, 24, 18, 96, 4, 54, 93, 20, 16, 97, 42, 77, -5, 34, 12, 72, 1, 106, -6, 79, -6, 22, 89, 10, 13, 74, 37, -4, 110, 9, -5, 32, 65, 80, 5, 31, -5, 45, 83, 80, 99, 82, 94, 76, 48, 18, 70, 29, 3, 45, 96, 6, 61, 38, 53, 8, 106, 22, 64, 41, -7, 58, 8, -2, -5, 10, 3, 67, 52, 109, 103, 110, 19, 44, 21, 62, 66, 87, 76, 22, 42, 54, -8, -5, 40, 4, 78, 20, 3, 13, 19, 17, 53, 47, 28, 68, 16, 100, 107, 78, 43, 52, 61, -3, 41, 54, 13, 2, 87, 35, 53, 102, 64, 26, 109, 36, -7, 73, 3, 28, 92, 72, -7, 45, 40, 49, 16, 62, 0, 25, 36, 103, 0, 82, 14, 60, 38, 47, 81, 38, 6, 6, 1, 93, 68, 106, 74, -6, 70, 84, 78, 51, 34, 46, 87, 23, 54, 48, 106, 88, 103, 91, 27, 19, 50, 22, 42, 72, 101, 61, 89, 3, 34, 111, 9, 41, -1, 1, 98, 110, 69, 6, 27, 19, 71, 73, 44, 54, 4, 56, 105, 82, 3, 53, 77, 22, 98, 46, 75, 39, 110, 85, 60, 8, 44, -5, 62, 97, 13, 52, 49, 40, 76, 103, 76, 48, 106, 31, 80, 70, 82, 93, 18, 66, 39, 71, 108, 67, -8, 47, 76, 97, 69, 89, -7, 104, 79, 64, 100, 97, 3, 89, 83, 15, 80, 61, 14, 88, 8, 64, 43, 21, 59, 47, 16, 107, 0, -9, 49, 91, 70, 82, 49, 72, 31, 23, 51, -6, 1, 81, 12, 81}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // placeholder22
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-9}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // param27
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_quant8_asymm_signed_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_three_symmetric_quant8_asymm_signed_all_inputs_as_internal", get_test_model_three_symmetric_quant8_asymm_signed_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_quant8_asymm_signed_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({106, 105, -2, 1, 91, 79, 71, 28, 64, 64, 61, 10, 43, 38, 78, 110, 105, 56, 44, 23, -5, -6, 47, 29, 37, 98, 54, 58, 19, -6, 30, 7, 52, 111, 72, 13, 98, 87, 79, 100, 83, 86, 33, 109, 106, 10, 81, 77, 46, 55, 50, 102, 51, 91, 33, 97, 99, 46, 59, 101, 78, 49, 18, 30, 75, 11, 100, 23, 100, 28, 106, 76, 52, 53, 69, 62, 28, 16, 52, 103, 66, 0, 89, 78, 100, 14, 80, -2, 69, 24, 18, 96, 4, 54, 93, 20, 16, 97, 42, 77, -5, 34, 12, 72, 1, 106, -6, 79, -6, 22, 89, 10, 13, 74, 37, -4, 110, 9, -5, 32, 65, 80, 5, 31, -5, 45, 83, 80, 99, 82, 94, 76, 48, 18, 70, 29, 3, 45, 96, 6, 61, 38, 53, 8, 106, 22, 64, 41, -7, 58, 8, -2, -5, 10, 3, 67, 52, 109, 103, 110, 19, 44, 21, 62, 66, 87, 76, 22, 42, 54, -8, -5, 40, 4, 78, 20, 3, 13, 19, 17, 53, 47, 28, 68, 16, 100, 107, 78, 43, 52, 61, -3, 41, 54, 13, 2, 87, 35, 53, 102, 64, 26, 109, 36, -7, 73, 3, 28, 92, 72, -7, 45, 40, 49, 16, 62, 0, 25, 36, 103, 0, 82, 14, 60, 38, 47, 81, 38, 6, 6, 1, 93, 68, 106, 74, -6, 70, 84, 78, 51, 34, 46, 87, 23, 54, 48, 106, 88, 103, 91, 27, 19, 50, 22, 42, 72, 101, 61, 89, 3, 34, 111, 9, 41, -1, 1, 98, 110, 69, 6, 27, 19, 71, 73, 44, 54, 4, 56, 105, 82, 3, 53, 77, 22, 98, 46, 75, 39, 110, 85, 60, 8, 44, -5, 62, 97, 13, 52, 49, 40, 76, 103, 76, 48, 106, 31, 80, 70, 82, 93, 18, 66, 39, 71, 108, 67, -8, 47, 76, 97, 69, 89, -7, 104, 79, 64, 100, 97, 3, 89, 83, 15, 80, 61, 14, 88, 8, 64, 43, 21, 59, 47, 16, 107, 0, -9, 49, 91, 70, 82, 49, 72, 31, 23, 51, -6, 1, 81, 12, 81}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({83, 83, 15, 80, 61, 14, 88, 88, 83, 83, 15, 80, 61, 14, 88, 88, 8, 8, 64, 43, 21, 59, 47, 47, 16, 16, 107, 0, -9, 49, 91, 91, 70, 70, 82, 49, 72, 31, 23, 23, 51, 51, -6, 1, 81, 12, 81, 81, 51, 51, -6, 1, 81, 12, 81, 81, 70, 70, 82, 49, 72, 31, 23, 23, 16, 16, 107, 0, -9, 49, 91, 91, 8, 8, 64, 43, 21, 59, 47, 47, 83, 83, 15, 80, 61, 14, 88, 88, 76, 76, 103, 76, 48, 106, 31, 31, 76, 76, 103, 76, 48, 106, 31, 31, 80, 80, 70, 82, 93, 18, 66, 66, 39, 39, 71, 108, 67, -8, 47, 47, 76, 76, 97, 69, 89, -7, 104, 104, 79, 79, 64, 100, 97, 3, 89, 89, 79, 79, 64, 100, 97, 3, 89, 89, 76, 76, 97, 69, 89, -7, 104, 104, 39, 39, 71, 108, 67, -8, 47, 47, 80, 80, 70, 82, 93, 18, 66, 66, 76, 76, 103, 76, 48, 106, 31, 31, 27, 27, 19, 71, 73, 44, 54, 54, 27, 27, 19, 71, 73, 44, 54, 54, 4, 4, 56, 105, 82, 3, 53, 53, 77, 77, 22, 98, 46, 75, 39, 39, 110, 110, 85, 60, 8, 44, -5, -5, 62, 62, 97, 13, 52, 49, 40, 40, 62, 62, 97, 13, 52, 49, 40, 40, 110, 110, 85, 60, 8, 44, -5, -5, 77, 77, 22, 98, 46, 75, 39, 39, 4, 4, 56, 105, 82, 3, 53, 53, 27, 27, 19, 71, 73, 44, 54, 54, 34, 34, 46, 87, 23, 54, 48, 48, 34, 34, 46, 87, 23, 54, 48, 48, 106, 106, 88, 103, 91, 27, 19, 19, 50, 50, 22, 42, 72, 101, 61, 61, 89, 89, 3, 34, 111, 9, 41, 41, -1, -1, 1, 98, 110, 69, 6, 6, -1, -1, 1, 98, 110, 69, 6, 6, 89, 89, 3, 34, 111, 9, 41, 41, 50, 50, 22, 42, 72, 101, 61, 61, 106, 106, 88, 103, 91, 27, 19, 19, 34, 34, 46, 87, 23, 54, 48, 48, 34, 34, 46, 87, 23, 54, 48, 48, 34, 34, 46, 87, 23, 54, 48, 48, 106, 106, 88, 103, 91, 27, 19, 19, 50, 50, 22, 42, 72, 101, 61, 61, 89, 89, 3, 34, 111, 9, 41, 41, -1, -1, 1, 98, 110, 69, 6, 6, -1, -1, 1, 98, 110, 69, 6, 6, 89, 89, 3, 34, 111, 9, 41, 41, 50, 50, 22, 42, 72, 101, 61, 61, 106, 106, 88, 103, 91, 27, 19, 19, 34, 34, 46, 87, 23, 54, 48, 48, 27, 27, 19, 71, 73, 44, 54, 54, 27, 27, 19, 71, 73, 44, 54, 54, 4, 4, 56, 105, 82, 3, 53, 53, 77, 77, 22, 98, 46, 75, 39, 39, 110, 110, 85, 60, 8, 44, -5, -5, 62, 62, 97, 13, 52, 49, 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44, 44, 23, -5, -6, 47, 29, 29, 43, 43, 38, 78, 110, 105, 56, 56, 71, 71, 28, 64, 64, 61, 10, 10, 106, 106, 105, -2, 1, 91, 79, 79, 30, 30, 7, 52, 111, 72, 13, 13, 30, 30, 7, 52, 111, 72, 13, 13, 98, 98, 87, 79, 100, 83, 86, 86, 33, 33, 109, 106, 10, 81, 77, 77, 46, 46, 55, 50, 102, 51, 91, 91, 33, 33, 97, 99, 46, 59, 101, 101, 33, 33, 97, 99, 46, 59, 101, 101, 46, 46, 55, 50, 102, 51, 91, 91, 33, 33, 109, 106, 10, 81, 77, 77, 98, 98, 87, 79, 100, 83, 86, 86, 30, 30, 7, 52, 111, 72, 13, 13, 78, 78, 49, 18, 30, 75, 11, 11, 78, 78, 49, 18, 30, 75, 11, 11, 100, 100, 23, 100, 28, 106, 76, 76, 52, 52, 53, 69, 62, 28, 16, 16, 52, 52, 103, 66, 0, 89, 78, 78, 100, 100, 14, 80, -2, 69, 24, 24, 100, 100, 14, 80, -2, 69, 24, 24, 52, 52, 103, 66, 0, 89, 78, 78, 52, 52, 53, 69, 62, 28, 16, 16, 100, 100, 23, 100, 28, 106, 76, 76, 78, 78, 49, 18, 30, 75, 11, 11, 18, 18, 96, 4, 54, 93, 20, 20, 18, 18, 96, 4, 54, 93, 20, 20, 16, 16, 97, 42, 77, -5, 34, 34, 12, 12, 72, 1, 106, -6, 79, 79, -6, -6, 22, 89, 10, 13, 74, 74, 37, 37, -4, 110, 9, -5, 32, 32, 37, 37, -4, 110, 9, -5, 32, 32, -6, -6, 22, 89, 10, 13, 74, 74, 12, 12, 72, 1, 106, -6, 79, 79, 16, 16, 97, 42, 77, -5, 34, 34, 18, 18, 96, 4, 54, 93, 20, 20, 18, 18, 96, 4, 54, 93, 20, 20, 18, 18, 96, 4, 54, 93, 20, 20, 16, 16, 97, 42, 77, -5, 34, 34, 12, 12, 72, 1, 106, -6, 79, 79, -6, -6, 22, 89, 10, 13, 74, 74, 37, 37, -4, 110, 9, -5, 32, 32, 37, 37, -4, 110, 9, -5, 32, 32, -6, -6, 22, 89, 10, 13, 74, 74, 12, 12, 72, 1, 106, -6, 79, 79, 16, 16, 97, 42, 77, -5, 34, 34, 18, 18, 96, 4, 54, 93, 20, 20, 78, 78, 49, 18, 30, 75, 11, 11, 78, 78, 49, 18, 30, 75, 11, 11, 100, 100, 23, 100, 28, 106, 76, 76, 52, 52, 53, 69, 62, 28, 16, 16, 52, 52, 103, 66, 0, 89, 78, 78, 100, 100, 14, 80, -2, 69, 24, 24, 100, 100, 14, 80, -2, 69, 24, 24, 52, 52, 103, 66, 0, 89, 78, 78, 52, 52, 53, 69, 62, 28, 16, 16, 100, 100, 23, 100, 28, 106, 76, 76, 78, 78, 49, 18, 30, 75, 11, 11}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_quant8_asymm_signed_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_three_symmetric_quant8_asymm_signed_all_tensors_as_inputs", get_test_model_three_symmetric_quant8_asymm_signed_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({83, 83, 15, 80, 61, 14, 88, 88, 83, 83, 15, 80, 61, 14, 88, 88, 8, 8, 64, 43, 21, 59, 47, 47, 16, 16, 107, 0, -9, 49, 91, 91, 70, 70, 82, 49, 72, 31, 23, 23, 51, 51, -6, 1, 81, 12, 81, 81, 51, 51, -6, 1, 81, 12, 81, 81, 70, 70, 82, 49, 72, 31, 23, 23, 16, 16, 107, 0, -9, 49, 91, 91, 8, 8, 64, 43, 21, 59, 47, 47, 83, 83, 15, 80, 61, 14, 88, 88, 76, 76, 103, 76, 48, 106, 31, 31, 76, 76, 103, 76, 48, 106, 31, 31, 80, 80, 70, 82, 93, 18, 66, 66, 39, 39, 71, 108, 67, -8, 47, 47, 76, 76, 97, 69, 89, -7, 104, 104, 79, 79, 64, 100, 97, 3, 89, 89, 79, 79, 64, 100, 97, 3, 89, 89, 76, 76, 97, 69, 89, -7, 104, 104, 39, 39, 71, 108, 67, -8, 47, 47, 80, 80, 70, 82, 93, 18, 66, 66, 76, 76, 103, 76, 48, 106, 31, 31, 27, 27, 19, 71, 73, 44, 54, 54, 27, 27, 19, 71, 73, 44, 54, 54, 4, 4, 56, 105, 82, 3, 53, 53, 77, 77, 22, 98, 46, 75, 39, 39, 110, 110, 85, 60, 8, 44, -5, -5, 62, 62, 97, 13, 52, 49, 40, 40, 62, 62, 97, 13, 52, 49, 40, 40, 110, 110, 85, 60, 8, 44, -5, -5, 77, 77, 22, 98, 46, 75, 39, 39, 4, 4, 56, 105, 82, 3, 53, 53, 27, 27, 19, 71, 73, 44, 54, 54, 34, 34, 46, 87, 23, 54, 48, 48, 34, 34, 46, 87, 23, 54, 48, 48, 106, 106, 88, 103, 91, 27, 19, 19, 50, 50, 22, 42, 72, 101, 61, 61, 89, 89, 3, 34, 111, 9, 41, 41, -1, -1, 1, 98, 110, 69, 6, 6, -1, -1, 1, 98, 110, 69, 6, 6, 89, 89, 3, 34, 111, 9, 41, 41, 50, 50, 22, 42, 72, 101, 61, 61, 106, 106, 88, 103, 91, 27, 19, 19, 34, 34, 46, 87, 23, 54, 48, 48, 34, 34, 46, 87, 23, 54, 48, 48, 34, 34, 46, 87, 23, 54, 48, 48, 106, 106, 88, 103, 91, 27, 19, 19, 50, 50, 22, 42, 72, 101, 61, 61, 89, 89, 3, 34, 111, 9, 41, 41, -1, -1, 1, 98, 110, 69, 6, 6, -1, -1, 1, 98, 110, 69, 6, 6, 89, 89, 3, 34, 111, 9, 41, 41, 50, 50, 22, 42, 72, 101, 61, 61, 106, 106, 88, 103, 91, 27, 19, 19, 34, 34, 46, 87, 23, 54, 48, 48, 27, 27, 19, 71, 73, 44, 54, 54, 27, 27, 19, 71, 73, 44, 54, 54, 4, 4, 56, 105, 82, 3, 53, 53, 77, 77, 22, 98, 46, 75, 39, 39, 110, 110, 85, 60, 8, 44, -5, -5, 62, 62, 97, 13, 52, 49, 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61, 106, 106, 88, 103, 91, 27, 19, 19, 34, 34, 46, 87, 23, 54, 48, 48, 27, 27, 19, 71, 73, 44, 54, 54, 27, 27, 19, 71, 73, 44, 54, 54, 4, 4, 56, 105, 82, 3, 53, 53, 77, 77, 22, 98, 46, 75, 39, 39, 110, 110, 85, 60, 8, 44, -5, -5, 62, 62, 97, 13, 52, 49, 40, 40, 62, 62, 97, 13, 52, 49, 40, 40, 110, 110, 85, 60, 8, 44, -5, -5, 77, 77, 22, 98, 46, 75, 39, 39, 4, 4, 56, 105, 82, 3, 53, 53, 27, 27, 19, 71, 73, 44, 54, 54, 76, 76, 103, 76, 48, 106, 31, 31, 76, 76, 103, 76, 48, 106, 31, 31, 80, 80, 70, 82, 93, 18, 66, 66, 39, 39, 71, 108, 67, -8, 47, 47, 76, 76, 97, 69, 89, -7, 104, 104, 79, 79, 64, 100, 97, 3, 89, 89, 79, 79, 64, 100, 97, 3, 89, 89, 76, 76, 97, 69, 89, -7, 104, 104, 39, 39, 71, 108, 67, -8, 47, 47, 80, 80, 70, 82, 93, 18, 66, 66, 76, 76, 103, 76, 48, 106, 31, 31, 83, 83, 15, 80, 61, 14, 88, 88, 83, 83, 15, 80, 61, 14, 88, 88, 8, 8, 64, 43, 21, 59, 47, 47, 16, 16, 107, 0, -9, 49, 91, 91, 70, 70, 82, 49, 72, 31, 23, 23, 51, 51, -6, 1, 81, 12, 81, 81, 51, 51, -6, 1, 81, 12, 81, 81, 70, 70, 82, 49, 72, 31, 23, 23, 16, 16, 107, 0, -9, 49, 91, 91, 8, 8, 64, 43, 21, 59, 47, 47, 83, 83, 15, 80, 61, 14, 88, 88, 83, 83, 15, 80, 61, 14, 88, 88, 83, 83, 15, 80, 61, 14, 88, 88, 8, 8, 64, 43, 21, 59, 47, 47, 16, 16, 107, 0, -9, 49, 91, 91, 70, 70, 82, 49, 72, 31, 23, 23, 51, 51, -6, 1, 81, 12, 81, 81, 51, 51, -6, 1, 81, 12, 81, 81, 70, 70, 82, 49, 72, 31, 23, 23, 16, 16, 107, 0, -9, 49, 91, 91, 8, 8, 64, 43, 21, 59, 47, 47, 83, 83, 15, 80, 61, 14, 88, 88, 76, 76, 103, 76, 48, 106, 31, 31, 76, 76, 103, 76, 48, 106, 31, 31, 80, 80, 70, 82, 93, 18, 66, 66, 39, 39, 71, 108, 67, -8, 47, 47, 76, 76, 97, 69, 89, -7, 104, 104, 79, 79, 64, 100, 97, 3, 89, 89, 79, 79, 64, 100, 97, 3, 89, 89, 76, 76, 97, 69, 89, -7, 104, 104, 39, 39, 71, 108, 67, -8, 47, 47, 80, 80, 70, 82, 93, 18, 66, 66, 76, 76, 103, 76, 48, 106, 31, 31, -7, -7, 45, 40, 49, 16, 62, 62, -7, -7, 45, 40, 49, 16, 62, 62, 0, 0, 25, 36, 103, 0, 82, 82, 14, 14, 60, 38, 47, 81, 38, 38, 6, 6, 6, 1, 93, 68, 106, 106, 74, 74, -6, 70, 84, 78, 51, 51, 74, 74, -6, 70, 84, 78, 51, 51, 6, 6, 6, 1, 93, 68, 106, 106, 14, 14, 60, 38, 47, 81, 38, 38, 0, 0, 25, 36, 103, 0, 82, 82, -7, -7, 45, 40, 49, 16, 62, 62, 53, 53, 47, 28, 68, 16, 100, 100, 53, 53, 47, 28, 68, 16, 100, 100, 107, 107, 78, 43, 52, 61, -3, -3, 41, 41, 54, 13, 2, 87, 35, 35, 53, 53, 102, 64, 26, 109, 36, 36, -7, -7, 73, 3, 28, 92, 72, 72, -7, -7, 73, 3, 28, 92, 72, 72, 53, 53, 102, 64, 26, 109, 36, 36, 41, 41, 54, 13, 2, 87, 35, 35, 107, 107, 78, 43, 52, 61, -3, -3, 53, 53, 47, 28, 68, 16, 100, 100, 8, 8, -2, -5, 10, 3, 67, 67, 8, 8, -2, -5, 10, 3, 67, 67, 52, 52, 109, 103, 110, 19, 44, 44, 21, 21, 62, 66, 87, 76, 22, 22, 42, 42, 54, -8, -5, 40, 4, 4, 78, 78, 20, 3, 13, 19, 17, 17, 78, 78, 20, 3, 13, 19, 17, 17, 42, 42, 54, -8, -5, 40, 4, 4, 21, 21, 62, 66, 87, 76, 22, 22, 52, 52, 109, 103, 110, 19, 44, 44, 8, 8, -2, -5, 10, 3, 67, 67, 65, 65, 80, 5, 31, -5, 45, 45, 65, 65, 80, 5, 31, -5, 45, 45, 83, 83, 80, 99, 82, 94, 76, 76, 48, 48, 18, 70, 29, 3, 45, 45, 96, 96, 6, 61, 38, 53, 8, 8, 106, 106, 22, 64, 41, -7, 58, 58, 106, 106, 22, 64, 41, -7, 58, 58, 96, 96, 6, 61, 38, 53, 8, 8, 48, 48, 18, 70, 29, 3, 45, 45, 83, 83, 80, 99, 82, 94, 76, 76, 65, 65, 80, 5, 31, -5, 45, 45, 65, 65, 80, 5, 31, -5, 45, 45, 65, 65, 80, 5, 31, -5, 45, 45, 83, 83, 80, 99, 82, 94, 76, 76, 48, 48, 18, 70, 29, 3, 45, 45, 96, 96, 6, 61, 38, 53, 8, 8, 106, 106, 22, 64, 41, -7, 58, 58, 106, 106, 22, 64, 41, -7, 58, 58, 96, 96, 6, 61, 38, 53, 8, 8, 48, 48, 18, 70, 29, 3, 45, 45, 83, 83, 80, 99, 82, 94, 76, 76, 65, 65, 80, 5, 31, -5, 45, 45, 8, 8, -2, -5, 10, 3, 67, 67, 8, 8, -2, -5, 10, 3, 67, 67, 52, 52, 109, 103, 110, 19, 44, 44, 21, 21, 62, 66, 87, 76, 22, 22, 42, 42, 54, -8, -5, 40, 4, 4, 78, 78, 20, 3, 13, 19, 17, 17, 78, 78, 20, 3, 13, 19, 17, 17, 42, 42, 54, -8, -5, 40, 4, 4, 21, 21, 62, 66, 87, 76, 22, 22, 52, 52, 109, 103, 110, 19, 44, 44, 8, 8, -2, -5, 10, 3, 67, 67, 53, 53, 47, 28, 68, 16, 100, 100, 53, 53, 47, 28, 68, 16, 100, 100, 107, 107, 78, 43, 52, 61, -3, -3, 41, 41, 54, 13, 2, 87, 35, 35, 53, 53, 102, 64, 26, 109, 36, 36, -7, -7, 73, 3, 28, 92, 72, 72, -7, -7, 73, 3, 28, 92, 72, 72, 53, 53, 102, 64, 26, 109, 36, 36, 41, 41, 54, 13, 2, 87, 35, 35, 107, 107, 78, 43, 52, 61, -3, -3, 53, 53, 47, 28, 68, 16, 100, 100, -7, -7, 45, 40, 49, 16, 62, 62, -7, -7, 45, 40, 49, 16, 62, 62, 0, 0, 25, 36, 103, 0, 82, 82, 14, 14, 60, 38, 47, 81, 38, 38, 6, 6, 6, 1, 93, 68, 106, 106, 74, 74, -6, 70, 84, 78, 51, 51, 74, 74, -6, 70, 84, 78, 51, 51, 6, 6, 6, 1, 93, 68, 106, 106, 14, 14, 60, 38, 47, 81, 38, 38, 0, 0, 25, 36, 103, 0, 82, 82, -7, -7, 45, 40, 49, 16, 62, 62, -7, -7, 45, 40, 49, 16, 62, 62, -7, -7, 45, 40, 49, 16, 62, 62, 0, 0, 25, 36, 103, 0, 82, 82, 14, 14, 60, 38, 47, 81, 38, 38, 6, 6, 6, 1, 93, 68, 106, 106, 74, 74, -6, 70, 84, 78, 51, 51, 74, 74, -6, 70, 84, 78, 51, 51, 6, 6, 6, 1, 93, 68, 106, 106, 14, 14, 60, 38, 47, 81, 38, 38, 0, 0, 25, 36, 103, 0, 82, 82, -7, -7, 45, 40, 49, 16, 62, 62, 53, 53, 47, 28, 68, 16, 100, 100, 53, 53, 47, 28, 68, 16, 100, 100, 107, 107, 78, 43, 52, 61, -3, -3, 41, 41, 54, 13, 2, 87, 35, 35, 53, 53, 102, 64, 26, 109, 36, 36, -7, -7, 73, 3, 28, 92, 72, 72, -7, -7, 73, 3, 28, 92, 72, 72, 53, 53, 102, 64, 26, 109, 36, 36, 41, 41, 54, 13, 2, 87, 35, 35, 107, 107, 78, 43, 52, 61, -3, -3, 53, 53, 47, 28, 68, 16, 100, 100, 18, 18, 96, 4, 54, 93, 20, 20, 18, 18, 96, 4, 54, 93, 20, 20, 16, 16, 97, 42, 77, -5, 34, 34, 12, 12, 72, 1, 106, -6, 79, 79, -6, -6, 22, 89, 10, 13, 74, 74, 37, 37, -4, 110, 9, -5, 32, 32, 37, 37, -4, 110, 9, -5, 32, 32, -6, -6, 22, 89, 10, 13, 74, 74, 12, 12, 72, 1, 106, -6, 79, 79, 16, 16, 97, 42, 77, -5, 34, 34, 18, 18, 96, 4, 54, 93, 20, 20, 78, 78, 49, 18, 30, 75, 11, 11, 78, 78, 49, 18, 30, 75, 11, 11, 100, 100, 23, 100, 28, 106, 76, 76, 52, 52, 53, 69, 62, 28, 16, 16, 52, 52, 103, 66, 0, 89, 78, 78, 100, 100, 14, 80, -2, 69, 24, 24, 100, 100, 14, 80, -2, 69, 24, 24, 52, 52, 103, 66, 0, 89, 78, 78, 52, 52, 53, 69, 62, 28, 16, 16, 100, 100, 23, 100, 28, 106, 76, 76, 78, 78, 49, 18, 30, 75, 11, 11, 30, 30, 7, 52, 111, 72, 13, 13, 30, 30, 7, 52, 111, 72, 13, 13, 98, 98, 87, 79, 100, 83, 86, 86, 33, 33, 109, 106, 10, 81, 77, 77, 46, 46, 55, 50, 102, 51, 91, 91, 33, 33, 97, 99, 46, 59, 101, 101, 33, 33, 97, 99, 46, 59, 101, 101, 46, 46, 55, 50, 102, 51, 91, 91, 33, 33, 109, 106, 10, 81, 77, 77, 98, 98, 87, 79, 100, 83, 86, 86, 30, 30, 7, 52, 111, 72, 13, 13, 106, 106, 105, -2, 1, 91, 79, 79, 106, 106, 105, -2, 1, 91, 79, 79, 71, 71, 28, 64, 64, 61, 10, 10, 43, 43, 38, 78, 110, 105, 56, 56, 44, 44, 23, -5, -6, 47, 29, 29, 37, 37, 98, 54, 58, 19, -6, -6, 37, 37, 98, 54, 58, 19, -6, -6, 44, 44, 23, -5, -6, 47, 29, 29, 43, 43, 38, 78, 110, 105, 56, 56, 71, 71, 28, 64, 64, 61, 10, 10, 106, 106, 105, -2, 1, 91, 79, 79, 106, 106, 105, -2, 1, 91, 79, 79, 106, 106, 105, -2, 1, 91, 79, 79, 71, 71, 28, 64, 64, 61, 10, 10, 43, 43, 38, 78, 110, 105, 56, 56, 44, 44, 23, -5, -6, 47, 29, 29, 37, 37, 98, 54, 58, 19, -6, -6, 37, 37, 98, 54, 58, 19, -6, -6, 44, 44, 23, -5, -6, 47, 29, 29, 43, 43, 38, 78, 110, 105, 56, 56, 71, 71, 28, 64, 64, 61, 10, 10, 106, 106, 105, -2, 1, 91, 79, 79, 30, 30, 7, 52, 111, 72, 13, 13, 30, 30, 7, 52, 111, 72, 13, 13, 98, 98, 87, 79, 100, 83, 86, 86, 33, 33, 109, 106, 10, 81, 77, 77, 46, 46, 55, 50, 102, 51, 91, 91, 33, 33, 97, 99, 46, 59, 101, 101, 33, 33, 97, 99, 46, 59, 101, 101, 46, 46, 55, 50, 102, 51, 91, 91, 33, 33, 109, 106, 10, 81, 77, 77, 98, 98, 87, 79, 100, 83, 86, 86, 30, 30, 7, 52, 111, 72, 13, 13, 78, 78, 49, 18, 30, 75, 11, 11, 78, 78, 49, 18, 30, 75, 11, 11, 100, 100, 23, 100, 28, 106, 76, 76, 52, 52, 53, 69, 62, 28, 16, 16, 52, 52, 103, 66, 0, 89, 78, 78, 100, 100, 14, 80, -2, 69, 24, 24, 100, 100, 14, 80, -2, 69, 24, 24, 52, 52, 103, 66, 0, 89, 78, 78, 52, 52, 53, 69, 62, 28, 16, 16, 100, 100, 23, 100, 28, 106, 76, 76, 78, 78, 49, 18, 30, 75, 11, 11, 18, 18, 96, 4, 54, 93, 20, 20, 18, 18, 96, 4, 54, 93, 20, 20, 16, 16, 97, 42, 77, -5, 34, 34, 12, 12, 72, 1, 106, -6, 79, 79, -6, -6, 22, 89, 10, 13, 74, 74, 37, 37, -4, 110, 9, -5, 32, 32, 37, 37, -4, 110, 9, -5, 32, 32, -6, -6, 22, 89, 10, 13, 74, 74, 12, 12, 72, 1, 106, -6, 79, 79, 16, 16, 97, 42, 77, -5, 34, 34, 18, 18, 96, 4, 54, 93, 20, 20, 18, 18, 96, 4, 54, 93, 20, 20, 18, 18, 96, 4, 54, 93, 20, 20, 16, 16, 97, 42, 77, -5, 34, 34, 12, 12, 72, 1, 106, -6, 79, 79, -6, -6, 22, 89, 10, 13, 74, 74, 37, 37, -4, 110, 9, -5, 32, 32, 37, 37, -4, 110, 9, -5, 32, 32, -6, -6, 22, 89, 10, 13, 74, 74, 12, 12, 72, 1, 106, -6, 79, 79, 16, 16, 97, 42, 77, -5, 34, 34, 18, 18, 96, 4, 54, 93, 20, 20, 78, 78, 49, 18, 30, 75, 11, 11, 78, 78, 49, 18, 30, 75, 11, 11, 100, 100, 23, 100, 28, 106, 76, 76, 52, 52, 53, 69, 62, 28, 16, 16, 52, 52, 103, 66, 0, 89, 78, 78, 100, 100, 14, 80, -2, 69, 24, 24, 100, 100, 14, 80, -2, 69, 24, 24, 52, 52, 103, 66, 0, 89, 78, 78, 52, 52, 53, 69, 62, 28, 16, 16, 100, 100, 23, 100, 28, 106, 76, 76, 78, 78, 49, 18, 30, 75, 11, 11}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // in4_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({106, 105, -2, 1, 91, 79, 71, 28, 64, 64, 61, 10, 43, 38, 78, 110, 105, 56, 44, 23, -5, -6, 47, 29, 37, 98, 54, 58, 19, -6, 30, 7, 52, 111, 72, 13, 98, 87, 79, 100, 83, 86, 33, 109, 106, 10, 81, 77, 46, 55, 50, 102, 51, 91, 33, 97, 99, 46, 59, 101, 78, 49, 18, 30, 75, 11, 100, 23, 100, 28, 106, 76, 52, 53, 69, 62, 28, 16, 52, 103, 66, 0, 89, 78, 100, 14, 80, -2, 69, 24, 18, 96, 4, 54, 93, 20, 16, 97, 42, 77, -5, 34, 12, 72, 1, 106, -6, 79, -6, 22, 89, 10, 13, 74, 37, -4, 110, 9, -5, 32, 65, 80, 5, 31, -5, 45, 83, 80, 99, 82, 94, 76, 48, 18, 70, 29, 3, 45, 96, 6, 61, 38, 53, 8, 106, 22, 64, 41, -7, 58, 8, -2, -5, 10, 3, 67, 52, 109, 103, 110, 19, 44, 21, 62, 66, 87, 76, 22, 42, 54, -8, -5, 40, 4, 78, 20, 3, 13, 19, 17, 53, 47, 28, 68, 16, 100, 107, 78, 43, 52, 61, -3, 41, 54, 13, 2, 87, 35, 53, 102, 64, 26, 109, 36, -7, 73, 3, 28, 92, 72, -7, 45, 40, 49, 16, 62, 0, 25, 36, 103, 0, 82, 14, 60, 38, 47, 81, 38, 6, 6, 1, 93, 68, 106, 74, -6, 70, 84, 78, 51, 34, 46, 87, 23, 54, 48, 106, 88, 103, 91, 27, 19, 50, 22, 42, 72, 101, 61, 89, 3, 34, 111, 9, 41, -1, 1, 98, 110, 69, 6, 27, 19, 71, 73, 44, 54, 4, 56, 105, 82, 3, 53, 77, 22, 98, 46, 75, 39, 110, 85, 60, 8, 44, -5, 62, 97, 13, 52, 49, 40, 76, 103, 76, 48, 106, 31, 80, 70, 82, 93, 18, 66, 39, 71, 108, 67, -8, 47, 76, 97, 69, 89, -7, 104, 79, 64, 100, 97, 3, 89, 83, 15, 80, 61, 14, 88, 8, 64, 43, 21, 59, 47, 16, 107, 0, -9, 49, 91, 70, 82, 49, 72, 31, 23, 51, -6, 1, 81, 12, 81}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // placeholder23
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-9}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // param28
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_three_symmetric_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_three_symmetric_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_int32() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({29, 28, 2, 3, 25, 22, 20, 9, 18, 18, 17, 5, 13, 12, 22, 30, 28, 16, 13, 8, 1, 1, 14, 10, 11, 27, 16, 17, 7, 1, 10, 4, 15, 30, 20, 5, 27, 24, 22, 27, 23, 24, 11, 29, 29, 5, 23, 21, 14, 16, 15, 28, 15, 25, 11, 26, 27, 14, 17, 28, 22, 15, 7, 10, 21, 5, 27, 8, 27, 9, 29, 21, 15, 16, 20, 18, 9, 6, 15, 28, 19, 2, 25, 22, 27, 6, 22, 2, 20, 8, 7, 26, 3, 16, 26, 7, 6, 26, 13, 22, 1, 11, 5, 20, 2, 29, 1, 22, 1, 8, 24, 5, 6, 21, 12, 1, 30, 5, 1, 10, 18, 22, 3, 10, 1, 13, 23, 22, 27, 23, 26, 21, 14, 7, 20, 9, 3, 13, 26, 4, 18, 12, 15, 4, 29, 8, 18, 13, 1, 17, 4, 2, 1, 5, 3, 19, 15, 30, 28, 30, 7, 13, 8, 18, 19, 24, 21, 8, 13, 16, 0, 1, 12, 3, 22, 7, 3, 5, 7, 7, 16, 14, 9, 19, 6, 27, 29, 22, 13, 15, 17, 2, 13, 16, 5, 3, 24, 11, 16, 28, 18, 9, 30, 11, 1, 21, 3, 9, 25, 20, 0, 14, 12, 15, 6, 18, 2, 9, 11, 28, 2, 23, 6, 17, 12, 14, 23, 12, 4, 4, 2, 26, 19, 29, 21, 1, 20, 23, 22, 15, 11, 14, 24, 8, 16, 14, 29, 24, 28, 25, 9, 7, 15, 8, 13, 20, 28, 18, 25, 3, 11, 30, 4, 13, 2, 3, 27, 30, 19, 4, 9, 7, 20, 20, 13, 16, 3, 16, 28, 23, 3, 15, 21, 8, 27, 14, 21, 12, 30, 23, 17, 4, 13, 1, 18, 26, 5, 15, 14, 12, 21, 28, 21, 14, 29, 10, 22, 20, 23, 26, 7, 19, 12, 20, 29, 19, 0, 14, 21, 26, 20, 24, 1, 28, 22, 18, 27, 27, 3, 24, 23, 6, 22, 18, 6, 24, 4, 18, 13, 8, 17, 14, 6, 29, 2, 0, 15, 25, 20, 23, 15, 20, 10, 8, 15, 1, 2, 23, 5, 23}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({23, 23, 6, 22, 18, 6, 24, 24, 23, 23, 6, 22, 18, 6, 24, 24, 4, 4, 18, 13, 8, 17, 14, 14, 6, 6, 29, 2, 0, 15, 25, 25, 20, 20, 23, 15, 20, 10, 8, 8, 15, 15, 1, 2, 23, 5, 23, 23, 15, 15, 1, 2, 23, 5, 23, 23, 20, 20, 23, 15, 20, 10, 8, 8, 6, 6, 29, 2, 0, 15, 25, 25, 4, 4, 18, 13, 8, 17, 14, 14, 23, 23, 6, 22, 18, 6, 24, 24, 21, 21, 28, 21, 14, 29, 10, 10, 21, 21, 28, 21, 14, 29, 10, 10, 22, 22, 20, 23, 26, 7, 19, 19, 12, 12, 20, 29, 19, 0, 14, 14, 21, 21, 26, 20, 24, 1, 28, 28, 22, 22, 18, 27, 27, 3, 24, 24, 22, 22, 18, 27, 27, 3, 24, 24, 21, 21, 26, 20, 24, 1, 28, 28, 12, 12, 20, 29, 19, 0, 14, 14, 22, 22, 20, 23, 26, 7, 19, 19, 21, 21, 28, 21, 14, 29, 10, 10, 9, 9, 7, 20, 20, 13, 16, 16, 9, 9, 7, 20, 20, 13, 16, 16, 3, 3, 16, 28, 23, 3, 15, 15, 21, 21, 8, 27, 14, 21, 12, 12, 30, 30, 23, 17, 4, 13, 1, 1, 18, 18, 26, 5, 15, 14, 12, 12, 18, 18, 26, 5, 15, 14, 12, 12, 30, 30, 23, 17, 4, 13, 1, 1, 21, 21, 8, 27, 14, 21, 12, 12, 3, 3, 16, 28, 23, 3, 15, 15, 9, 9, 7, 20, 20, 13, 16, 16, 11, 11, 14, 24, 8, 16, 14, 14, 11, 11, 14, 24, 8, 16, 14, 14, 29, 29, 24, 28, 25, 9, 7, 7, 15, 15, 8, 13, 20, 28, 18, 18, 25, 25, 3, 11, 30, 4, 13, 13, 2, 2, 3, 27, 30, 19, 4, 4, 2, 2, 3, 27, 30, 19, 4, 4, 25, 25, 3, 11, 30, 4, 13, 13, 15, 15, 8, 13, 20, 28, 18, 18, 29, 29, 24, 28, 25, 9, 7, 7, 11, 11, 14, 24, 8, 16, 14, 14, 11, 11, 14, 24, 8, 16, 14, 14, 11, 11, 14, 24, 8, 16, 14, 14, 29, 29, 24, 28, 25, 9, 7, 7, 15, 15, 8, 13, 20, 28, 18, 18, 25, 25, 3, 11, 30, 4, 13, 13, 2, 2, 3, 27, 30, 19, 4, 4, 2, 2, 3, 27, 30, 19, 4, 4, 25, 25, 3, 11, 30, 4, 13, 13, 15, 15, 8, 13, 20, 28, 18, 18, 29, 29, 24, 28, 25, 9, 7, 7, 11, 11, 14, 24, 8, 16, 14, 14, 9, 9, 7, 20, 20, 13, 16, 16, 9, 9, 7, 20, 20, 13, 16, 16, 3, 3, 16, 28, 23, 3, 15, 15, 21, 21, 8, 27, 14, 21, 12, 12, 30, 30, 23, 17, 4, 13, 1, 1, 18, 18, 26, 5, 15, 14, 12, 12, 18, 18, 26, 5, 15, 14, 12, 12, 30, 30, 23, 17, 4, 13, 1, 1, 21, 21, 8, 27, 14, 21, 12, 12, 3, 3, 16, 28, 23, 3, 15, 15, 9, 9, 7, 20, 20, 13, 16, 16, 21, 21, 28, 21, 14, 29, 10, 10, 21, 21, 28, 21, 14, 29, 10, 10, 22, 22, 20, 23, 26, 7, 19, 19, 12, 12, 20, 29, 19, 0, 14, 14, 21, 21, 26, 20, 24, 1, 28, 28, 22, 22, 18, 27, 27, 3, 24, 24, 22, 22, 18, 27, 27, 3, 24, 24, 21, 21, 26, 20, 24, 1, 28, 28, 12, 12, 20, 29, 19, 0, 14, 14, 22, 22, 20, 23, 26, 7, 19, 19, 21, 21, 28, 21, 14, 29, 10, 10, 23, 23, 6, 22, 18, 6, 24, 24, 23, 23, 6, 22, 18, 6, 24, 24, 4, 4, 18, 13, 8, 17, 14, 14, 6, 6, 29, 2, 0, 15, 25, 25, 20, 20, 23, 15, 20, 10, 8, 8, 15, 15, 1, 2, 23, 5, 23, 23, 15, 15, 1, 2, 23, 5, 23, 23, 20, 20, 23, 15, 20, 10, 8, 8, 6, 6, 29, 2, 0, 15, 25, 25, 4, 4, 18, 13, 8, 17, 14, 14, 23, 23, 6, 22, 18, 6, 24, 24, 23, 23, 6, 22, 18, 6, 24, 24, 23, 23, 6, 22, 18, 6, 24, 24, 4, 4, 18, 13, 8, 17, 14, 14, 6, 6, 29, 2, 0, 15, 25, 25, 20, 20, 23, 15, 20, 10, 8, 8, 15, 15, 1, 2, 23, 5, 23, 23, 15, 15, 1, 2, 23, 5, 23, 23, 20, 20, 23, 15, 20, 10, 8, 8, 6, 6, 29, 2, 0, 15, 25, 25, 4, 4, 18, 13, 8, 17, 14, 14, 23, 23, 6, 22, 18, 6, 24, 24, 21, 21, 28, 21, 14, 29, 10, 10, 21, 21, 28, 21, 14, 29, 10, 10, 22, 22, 20, 23, 26, 7, 19, 19, 12, 12, 20, 29, 19, 0, 14, 14, 21, 21, 26, 20, 24, 1, 28, 28, 22, 22, 18, 27, 27, 3, 24, 24, 22, 22, 18, 27, 27, 3, 24, 24, 21, 21, 26, 20, 24, 1, 28, 28, 12, 12, 20, 29, 19, 0, 14, 14, 22, 22, 20, 23, 26, 7, 19, 19, 21, 21, 28, 21, 14, 29, 10, 10, 0, 0, 14, 12, 15, 6, 18, 18, 0, 0, 14, 12, 15, 6, 18, 18, 2, 2, 9, 11, 28, 2, 23, 23, 6, 6, 17, 12, 14, 23, 12, 12, 4, 4, 4, 2, 26, 19, 29, 29, 21, 21, 1, 20, 23, 22, 15, 15, 21, 21, 1, 20, 23, 22, 15, 15, 4, 4, 4, 2, 26, 19, 29, 29, 6, 6, 17, 12, 14, 23, 12, 12, 2, 2, 9, 11, 28, 2, 23, 23, 0, 0, 14, 12, 15, 6, 18, 18, 16, 16, 14, 9, 19, 6, 27, 27, 16, 16, 14, 9, 19, 6, 27, 27, 29, 29, 22, 13, 15, 17, 2, 2, 13, 13, 16, 5, 3, 24, 11, 11, 16, 16, 28, 18, 9, 30, 11, 11, 1, 1, 21, 3, 9, 25, 20, 20, 1, 1, 21, 3, 9, 25, 20, 20, 16, 16, 28, 18, 9, 30, 11, 11, 13, 13, 16, 5, 3, 24, 11, 11, 29, 29, 22, 13, 15, 17, 2, 2, 16, 16, 14, 9, 19, 6, 27, 27, 4, 4, 2, 1, 5, 3, 19, 19, 4, 4, 2, 1, 5, 3, 19, 19, 15, 15, 30, 28, 30, 7, 13, 13, 8, 8, 18, 19, 24, 21, 8, 8, 13, 13, 16, 0, 1, 12, 3, 3, 22, 22, 7, 3, 5, 7, 7, 7, 22, 22, 7, 3, 5, 7, 7, 7, 13, 13, 16, 0, 1, 12, 3, 3, 8, 8, 18, 19, 24, 21, 8, 8, 15, 15, 30, 28, 30, 7, 13, 13, 4, 4, 2, 1, 5, 3, 19, 19, 18, 18, 22, 3, 10, 1, 13, 13, 18, 18, 22, 3, 10, 1, 13, 13, 23, 23, 22, 27, 23, 26, 21, 21, 14, 14, 7, 20, 9, 3, 13, 13, 26, 26, 4, 18, 12, 15, 4, 4, 29, 29, 8, 18, 13, 1, 17, 17, 29, 29, 8, 18, 13, 1, 17, 17, 26, 26, 4, 18, 12, 15, 4, 4, 14, 14, 7, 20, 9, 3, 13, 13, 23, 23, 22, 27, 23, 26, 21, 21, 18, 18, 22, 3, 10, 1, 13, 13, 18, 18, 22, 3, 10, 1, 13, 13, 18, 18, 22, 3, 10, 1, 13, 13, 23, 23, 22, 27, 23, 26, 21, 21, 14, 14, 7, 20, 9, 3, 13, 13, 26, 26, 4, 18, 12, 15, 4, 4, 29, 29, 8, 18, 13, 1, 17, 17, 29, 29, 8, 18, 13, 1, 17, 17, 26, 26, 4, 18, 12, 15, 4, 4, 14, 14, 7, 20, 9, 3, 13, 13, 23, 23, 22, 27, 23, 26, 21, 21, 18, 18, 22, 3, 10, 1, 13, 13, 4, 4, 2, 1, 5, 3, 19, 19, 4, 4, 2, 1, 5, 3, 19, 19, 15, 15, 30, 28, 30, 7, 13, 13, 8, 8, 18, 19, 24, 21, 8, 8, 13, 13, 16, 0, 1, 12, 3, 3, 22, 22, 7, 3, 5, 7, 7, 7, 22, 22, 7, 3, 5, 7, 7, 7, 13, 13, 16, 0, 1, 12, 3, 3, 8, 8, 18, 19, 24, 21, 8, 8, 15, 15, 30, 28, 30, 7, 13, 13, 4, 4, 2, 1, 5, 3, 19, 19, 16, 16, 14, 9, 19, 6, 27, 27, 16, 16, 14, 9, 19, 6, 27, 27, 29, 29, 22, 13, 15, 17, 2, 2, 13, 13, 16, 5, 3, 24, 11, 11, 16, 16, 28, 18, 9, 30, 11, 11, 1, 1, 21, 3, 9, 25, 20, 20, 1, 1, 21, 3, 9, 25, 20, 20, 16, 16, 28, 18, 9, 30, 11, 11, 13, 13, 16, 5, 3, 24, 11, 11, 29, 29, 22, 13, 15, 17, 2, 2, 16, 16, 14, 9, 19, 6, 27, 27, 0, 0, 14, 12, 15, 6, 18, 18, 0, 0, 14, 12, 15, 6, 18, 18, 2, 2, 9, 11, 28, 2, 23, 23, 6, 6, 17, 12, 14, 23, 12, 12, 4, 4, 4, 2, 26, 19, 29, 29, 21, 21, 1, 20, 23, 22, 15, 15, 21, 21, 1, 20, 23, 22, 15, 15, 4, 4, 4, 2, 26, 19, 29, 29, 6, 6, 17, 12, 14, 23, 12, 12, 2, 2, 9, 11, 28, 2, 23, 23, 0, 0, 14, 12, 15, 6, 18, 18, 0, 0, 14, 12, 15, 6, 18, 18, 0, 0, 14, 12, 15, 6, 18, 18, 2, 2, 9, 11, 28, 2, 23, 23, 6, 6, 17, 12, 14, 23, 12, 12, 4, 4, 4, 2, 26, 19, 29, 29, 21, 21, 1, 20, 23, 22, 15, 15, 21, 21, 1, 20, 23, 22, 15, 15, 4, 4, 4, 2, 26, 19, 29, 29, 6, 6, 17, 12, 14, 23, 12, 12, 2, 2, 9, 11, 28, 2, 23, 23, 0, 0, 14, 12, 15, 6, 18, 18, 16, 16, 14, 9, 19, 6, 27, 27, 16, 16, 14, 9, 19, 6, 27, 27, 29, 29, 22, 13, 15, 17, 2, 2, 13, 13, 16, 5, 3, 24, 11, 11, 16, 16, 28, 18, 9, 30, 11, 11, 1, 1, 21, 3, 9, 25, 20, 20, 1, 1, 21, 3, 9, 25, 20, 20, 16, 16, 28, 18, 9, 30, 11, 11, 13, 13, 16, 5, 3, 24, 11, 11, 29, 29, 22, 13, 15, 17, 2, 2, 16, 16, 14, 9, 19, 6, 27, 27, 7, 7, 26, 3, 16, 26, 7, 7, 7, 7, 26, 3, 16, 26, 7, 7, 6, 6, 26, 13, 22, 1, 11, 11, 5, 5, 20, 2, 29, 1, 22, 22, 1, 1, 8, 24, 5, 6, 21, 21, 12, 12, 1, 30, 5, 1, 10, 10, 12, 12, 1, 30, 5, 1, 10, 10, 1, 1, 8, 24, 5, 6, 21, 21, 5, 5, 20, 2, 29, 1, 22, 22, 6, 6, 26, 13, 22, 1, 11, 11, 7, 7, 26, 3, 16, 26, 7, 7, 22, 22, 15, 7, 10, 21, 5, 5, 22, 22, 15, 7, 10, 21, 5, 5, 27, 27, 8, 27, 9, 29, 21, 21, 15, 15, 16, 20, 18, 9, 6, 6, 15, 15, 28, 19, 2, 25, 22, 22, 27, 27, 6, 22, 2, 20, 8, 8, 27, 27, 6, 22, 2, 20, 8, 8, 15, 15, 28, 19, 2, 25, 22, 22, 15, 15, 16, 20, 18, 9, 6, 6, 27, 27, 8, 27, 9, 29, 21, 21, 22, 22, 15, 7, 10, 21, 5, 5, 10, 10, 4, 15, 30, 20, 5, 5, 10, 10, 4, 15, 30, 20, 5, 5, 27, 27, 24, 22, 27, 23, 24, 24, 11, 11, 29, 29, 5, 23, 21, 21, 14, 14, 16, 15, 28, 15, 25, 25, 11, 11, 26, 27, 14, 17, 28, 28, 11, 11, 26, 27, 14, 17, 28, 28, 14, 14, 16, 15, 28, 15, 25, 25, 11, 11, 29, 29, 5, 23, 21, 21, 27, 27, 24, 22, 27, 23, 24, 24, 10, 10, 4, 15, 30, 20, 5, 5, 29, 29, 28, 2, 3, 25, 22, 22, 29, 29, 28, 2, 3, 25, 22, 22, 20, 20, 9, 18, 18, 17, 5, 5, 13, 13, 12, 22, 30, 28, 16, 16, 13, 13, 8, 1, 1, 14, 10, 10, 11, 11, 27, 16, 17, 7, 1, 1, 11, 11, 27, 16, 17, 7, 1, 1, 13, 13, 8, 1, 1, 14, 10, 10, 13, 13, 12, 22, 30, 28, 16, 16, 20, 20, 9, 18, 18, 17, 5, 5, 29, 29, 28, 2, 3, 25, 22, 22, 29, 29, 28, 2, 3, 25, 22, 22, 29, 29, 28, 2, 3, 25, 22, 22, 20, 20, 9, 18, 18, 17, 5, 5, 13, 13, 12, 22, 30, 28, 16, 16, 13, 13, 8, 1, 1, 14, 10, 10, 11, 11, 27, 16, 17, 7, 1, 1, 11, 11, 27, 16, 17, 7, 1, 1, 13, 13, 8, 1, 1, 14, 10, 10, 13, 13, 12, 22, 30, 28, 16, 16, 20, 20, 9, 18, 18, 17, 5, 5, 29, 29, 28, 2, 3, 25, 22, 22, 10, 10, 4, 15, 30, 20, 5, 5, 10, 10, 4, 15, 30, 20, 5, 5, 27, 27, 24, 22, 27, 23, 24, 24, 11, 11, 29, 29, 5, 23, 21, 21, 14, 14, 16, 15, 28, 15, 25, 25, 11, 11, 26, 27, 14, 17, 28, 28, 11, 11, 26, 27, 14, 17, 28, 28, 14, 14, 16, 15, 28, 15, 25, 25, 11, 11, 29, 29, 5, 23, 21, 21, 27, 27, 24, 22, 27, 23, 24, 24, 10, 10, 4, 15, 30, 20, 5, 5, 22, 22, 15, 7, 10, 21, 5, 5, 22, 22, 15, 7, 10, 21, 5, 5, 27, 27, 8, 27, 9, 29, 21, 21, 15, 15, 16, 20, 18, 9, 6, 6, 15, 15, 28, 19, 2, 25, 22, 22, 27, 27, 6, 22, 2, 20, 8, 8, 27, 27, 6, 22, 2, 20, 8, 8, 15, 15, 28, 19, 2, 25, 22, 22, 15, 15, 16, 20, 18, 9, 6, 6, 27, 27, 8, 27, 9, 29, 21, 21, 22, 22, 15, 7, 10, 21, 5, 5, 7, 7, 26, 3, 16, 26, 7, 7, 7, 7, 26, 3, 16, 26, 7, 7, 6, 6, 26, 13, 22, 1, 11, 11, 5, 5, 20, 2, 29, 1, 22, 22, 1, 1, 8, 24, 5, 6, 21, 21, 12, 12, 1, 30, 5, 1, 10, 10, 12, 12, 1, 30, 5, 1, 10, 10, 1, 1, 8, 24, 5, 6, 21, 21, 5, 5, 20, 2, 29, 1, 22, 22, 6, 6, 26, 13, 22, 1, 11, 11, 7, 7, 26, 3, 16, 26, 7, 7, 7, 7, 26, 3, 16, 26, 7, 7, 7, 7, 26, 3, 16, 26, 7, 7, 6, 6, 26, 13, 22, 1, 11, 11, 5, 5, 20, 2, 29, 1, 22, 22, 1, 1, 8, 24, 5, 6, 21, 21, 12, 12, 1, 30, 5, 1, 10, 10, 12, 12, 1, 30, 5, 1, 10, 10, 1, 1, 8, 24, 5, 6, 21, 21, 5, 5, 20, 2, 29, 1, 22, 22, 6, 6, 26, 13, 22, 1, 11, 11, 7, 7, 26, 3, 16, 26, 7, 7, 22, 22, 15, 7, 10, 21, 5, 5, 22, 22, 15, 7, 10, 21, 5, 5, 27, 27, 8, 27, 9, 29, 21, 21, 15, 15, 16, 20, 18, 9, 6, 6, 15, 15, 28, 19, 2, 25, 22, 22, 27, 27, 6, 22, 2, 20, 8, 8, 27, 27, 6, 22, 2, 20, 8, 8, 15, 15, 28, 19, 2, 25, 22, 22, 15, 15, 16, 20, 18, 9, 6, 6, 27, 27, 8, 27, 9, 29, 21, 21, 22, 22, 15, 7, 10, 21, 5, 5, 7, 7, 26, 3, 16, 26, 7, 7, 7, 7, 26, 3, 16, 26, 7, 7, 6, 6, 26, 13, 22, 1, 11, 11, 5, 5, 20, 2, 29, 1, 22, 22, 1, 1, 8, 24, 5, 6, 21, 21, 12, 12, 1, 30, 5, 1, 10, 10, 12, 12, 1, 30, 5, 1, 10, 10, 1, 1, 8, 24, 5, 6, 21, 21, 5, 5, 20, 2, 29, 1, 22, 22, 6, 6, 26, 13, 22, 1, 11, 11, 7, 7, 26, 3, 16, 26, 7, 7, 22, 22, 15, 7, 10, 21, 5, 5, 22, 22, 15, 7, 10, 21, 5, 5, 27, 27, 8, 27, 9, 29, 21, 21, 15, 15, 16, 20, 18, 9, 6, 6, 15, 15, 28, 19, 2, 25, 22, 22, 27, 27, 6, 22, 2, 20, 8, 8, 27, 27, 6, 22, 2, 20, 8, 8, 15, 15, 28, 19, 2, 25, 22, 22, 15, 15, 16, 20, 18, 9, 6, 6, 27, 27, 8, 27, 9, 29, 21, 21, 22, 22, 15, 7, 10, 21, 5, 5, 10, 10, 4, 15, 30, 20, 5, 5, 10, 10, 4, 15, 30, 20, 5, 5, 27, 27, 24, 22, 27, 23, 24, 24, 11, 11, 29, 29, 5, 23, 21, 21, 14, 14, 16, 15, 28, 15, 25, 25, 11, 11, 26, 27, 14, 17, 28, 28, 11, 11, 26, 27, 14, 17, 28, 28, 14, 14, 16, 15, 28, 15, 25, 25, 11, 11, 29, 29, 5, 23, 21, 21, 27, 27, 24, 22, 27, 23, 24, 24, 10, 10, 4, 15, 30, 20, 5, 5, 29, 29, 28, 2, 3, 25, 22, 22, 29, 29, 28, 2, 3, 25, 22, 22, 20, 20, 9, 18, 18, 17, 5, 5, 13, 13, 12, 22, 30, 28, 16, 16, 13, 13, 8, 1, 1, 14, 10, 10, 11, 11, 27, 16, 17, 7, 1, 1, 11, 11, 27, 16, 17, 7, 1, 1, 13, 13, 8, 1, 1, 14, 10, 10, 13, 13, 12, 22, 30, 28, 16, 16, 20, 20, 9, 18, 18, 17, 5, 5, 29, 29, 28, 2, 3, 25, 22, 22, 29, 29, 28, 2, 3, 25, 22, 22, 29, 29, 28, 2, 3, 25, 22, 22, 20, 20, 9, 18, 18, 17, 5, 5, 13, 13, 12, 22, 30, 28, 16, 16, 13, 13, 8, 1, 1, 14, 10, 10, 11, 11, 27, 16, 17, 7, 1, 1, 11, 11, 27, 16, 17, 7, 1, 1, 13, 13, 8, 1, 1, 14, 10, 10, 13, 13, 12, 22, 30, 28, 16, 16, 20, 20, 9, 18, 18, 17, 5, 5, 29, 29, 28, 2, 3, 25, 22, 22, 10, 10, 4, 15, 30, 20, 5, 5, 10, 10, 4, 15, 30, 20, 5, 5, 27, 27, 24, 22, 27, 23, 24, 24, 11, 11, 29, 29, 5, 23, 21, 21, 14, 14, 16, 15, 28, 15, 25, 25, 11, 11, 26, 27, 14, 17, 28, 28, 11, 11, 26, 27, 14, 17, 28, 28, 14, 14, 16, 15, 28, 15, 25, 25, 11, 11, 29, 29, 5, 23, 21, 21, 27, 27, 24, 22, 27, 23, 24, 24, 10, 10, 4, 15, 30, 20, 5, 5, 22, 22, 15, 7, 10, 21, 5, 5, 22, 22, 15, 7, 10, 21, 5, 5, 27, 27, 8, 27, 9, 29, 21, 21, 15, 15, 16, 20, 18, 9, 6, 6, 15, 15, 28, 19, 2, 25, 22, 22, 27, 27, 6, 22, 2, 20, 8, 8, 27, 27, 6, 22, 2, 20, 8, 8, 15, 15, 28, 19, 2, 25, 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27, 23, 24, 24, 10, 10, 4, 15, 30, 20, 5, 5, 29, 29, 28, 2, 3, 25, 22, 22, 29, 29, 28, 2, 3, 25, 22, 22, 20, 20, 9, 18, 18, 17, 5, 5, 13, 13, 12, 22, 30, 28, 16, 16, 13, 13, 8, 1, 1, 14, 10, 10, 11, 11, 27, 16, 17, 7, 1, 1, 11, 11, 27, 16, 17, 7, 1, 1, 13, 13, 8, 1, 1, 14, 10, 10, 13, 13, 12, 22, 30, 28, 16, 16, 20, 20, 9, 18, 18, 17, 5, 5, 29, 29, 28, 2, 3, 25, 22, 22, 29, 29, 28, 2, 3, 25, 22, 22, 29, 29, 28, 2, 3, 25, 22, 22, 20, 20, 9, 18, 18, 17, 5, 5, 13, 13, 12, 22, 30, 28, 16, 16, 13, 13, 8, 1, 1, 14, 10, 10, 11, 11, 27, 16, 17, 7, 1, 1, 11, 11, 27, 16, 17, 7, 1, 1, 13, 13, 8, 1, 1, 14, 10, 10, 13, 13, 12, 22, 30, 28, 16, 16, 20, 20, 9, 18, 18, 17, 5, 5, 29, 29, 28, 2, 3, 25, 22, 22, 10, 10, 4, 15, 30, 20, 5, 5, 10, 10, 4, 15, 30, 20, 5, 5, 27, 27, 24, 22, 27, 23, 24, 24, 11, 11, 29, 29, 5, 23, 21, 21, 14, 14, 16, 15, 28, 15, 25, 25, 11, 11, 26, 27, 14, 17, 28, 28, 11, 11, 26, 27, 14, 17, 28, 28, 14, 14, 16, 15, 28, 15, 25, 25, 11, 11, 29, 29, 5, 23, 21, 21, 27, 27, 24, 22, 27, 23, 24, 24, 10, 10, 4, 15, 30, 20, 5, 5, 22, 22, 15, 7, 10, 21, 5, 5, 22, 22, 15, 7, 10, 21, 5, 5, 27, 27, 8, 27, 9, 29, 21, 21, 15, 15, 16, 20, 18, 9, 6, 6, 15, 15, 28, 19, 2, 25, 22, 22, 27, 27, 6, 22, 2, 20, 8, 8, 27, 27, 6, 22, 2, 20, 8, 8, 15, 15, 28, 19, 2, 25, 22, 22, 15, 15, 16, 20, 18, 9, 6, 6, 27, 27, 8, 27, 9, 29, 21, 21, 22, 22, 15, 7, 10, 21, 5, 5, 7, 7, 26, 3, 16, 26, 7, 7, 7, 7, 26, 3, 16, 26, 7, 7, 6, 6, 26, 13, 22, 1, 11, 11, 5, 5, 20, 2, 29, 1, 22, 22, 1, 1, 8, 24, 5, 6, 21, 21, 12, 12, 1, 30, 5, 1, 10, 10, 12, 12, 1, 30, 5, 1, 10, 10, 1, 1, 8, 24, 5, 6, 21, 21, 5, 5, 20, 2, 29, 1, 22, 22, 6, 6, 26, 13, 22, 1, 11, 11, 7, 7, 26, 3, 16, 26, 7, 7, 7, 7, 26, 3, 16, 26, 7, 7, 7, 7, 26, 3, 16, 26, 7, 7, 6, 6, 26, 13, 22, 1, 11, 11, 5, 5, 20, 2, 29, 1, 22, 22, 1, 1, 8, 24, 5, 6, 21, 21, 12, 12, 1, 30, 5, 1, 10, 10, 12, 12, 1, 30, 5, 1, 10, 10, 1, 1, 8, 24, 5, 6, 21, 21, 5, 5, 20, 2, 29, 1, 22, 22, 6, 6, 26, 13, 22, 1, 11, 11, 7, 7, 26, 3, 16, 26, 7, 7, 22, 22, 15, 7, 10, 21, 5, 5, 22, 22, 15, 7, 10, 21, 5, 5, 27, 27, 8, 27, 9, 29, 21, 21, 15, 15, 16, 20, 18, 9, 6, 6, 15, 15, 28, 19, 2, 25, 22, 22, 27, 27, 6, 22, 2, 20, 8, 8, 27, 27, 6, 22, 2, 20, 8, 8, 15, 15, 28, 19, 2, 25, 22, 22, 15, 15, 16, 20, 18, 9, 6, 6, 27, 27, 8, 27, 9, 29, 21, 21, 22, 22, 15, 7, 10, 21, 5, 5}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_int32 = TestModelManager::get().add("mirror_pad_three_symmetric_int32", get_test_model_three_symmetric_int32());
+
+} // namespace generated_tests::mirror_pad
+
+namespace generated_tests::mirror_pad {
+
+const TestModel& get_test_model_three_symmetric_int32_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // in4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({29, 28, 2, 3, 25, 22, 20, 9, 18, 18, 17, 5, 13, 12, 22, 30, 28, 16, 13, 8, 1, 1, 14, 10, 11, 27, 16, 17, 7, 1, 10, 4, 15, 30, 20, 5, 27, 24, 22, 27, 23, 24, 11, 29, 29, 5, 23, 21, 14, 16, 15, 28, 15, 25, 11, 26, 27, 14, 17, 28, 22, 15, 7, 10, 21, 5, 27, 8, 27, 9, 29, 21, 15, 16, 20, 18, 9, 6, 15, 28, 19, 2, 25, 22, 27, 6, 22, 2, 20, 8, 7, 26, 3, 16, 26, 7, 6, 26, 13, 22, 1, 11, 5, 20, 2, 29, 1, 22, 1, 8, 24, 5, 6, 21, 12, 1, 30, 5, 1, 10, 18, 22, 3, 10, 1, 13, 23, 22, 27, 23, 26, 21, 14, 7, 20, 9, 3, 13, 26, 4, 18, 12, 15, 4, 29, 8, 18, 13, 1, 17, 4, 2, 1, 5, 3, 19, 15, 30, 28, 30, 7, 13, 8, 18, 19, 24, 21, 8, 13, 16, 0, 1, 12, 3, 22, 7, 3, 5, 7, 7, 16, 14, 9, 19, 6, 27, 29, 22, 13, 15, 17, 2, 13, 16, 5, 3, 24, 11, 16, 28, 18, 9, 30, 11, 1, 21, 3, 9, 25, 20, 0, 14, 12, 15, 6, 18, 2, 9, 11, 28, 2, 23, 6, 17, 12, 14, 23, 12, 4, 4, 2, 26, 19, 29, 21, 1, 20, 23, 22, 15, 11, 14, 24, 8, 16, 14, 29, 24, 28, 25, 9, 7, 15, 8, 13, 20, 28, 18, 25, 3, 11, 30, 4, 13, 2, 3, 27, 30, 19, 4, 9, 7, 20, 20, 13, 16, 3, 16, 28, 23, 3, 15, 21, 8, 27, 14, 21, 12, 30, 23, 17, 4, 13, 1, 18, 26, 5, 15, 14, 12, 21, 28, 21, 14, 29, 10, 22, 20, 23, 26, 7, 19, 12, 20, 29, 19, 0, 14, 21, 26, 20, 24, 1, 28, 22, 18, 27, 27, 3, 24, 23, 6, 22, 18, 6, 24, 4, 18, 13, 8, 17, 14, 6, 29, 2, 0, 15, 25, 20, 23, 15, 20, 10, 8, 15, 1, 2, 23, 5, 23}),
+ .dimensions = {3, 4, 5, 6},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // padding4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({3, 3, 4, 2, 1, 5, 1, 1}),
+ .dimensions = {4, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // out4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({23, 23, 6, 22, 18, 6, 24, 24, 23, 23, 6, 22, 18, 6, 24, 24, 4, 4, 18, 13, 8, 17, 14, 14, 6, 6, 29, 2, 0, 15, 25, 25, 20, 20, 23, 15, 20, 10, 8, 8, 15, 15, 1, 2, 23, 5, 23, 23, 15, 15, 1, 2, 23, 5, 23, 23, 20, 20, 23, 15, 20, 10, 8, 8, 6, 6, 29, 2, 0, 15, 25, 25, 4, 4, 18, 13, 8, 17, 14, 14, 23, 23, 6, 22, 18, 6, 24, 24, 21, 21, 28, 21, 14, 29, 10, 10, 21, 21, 28, 21, 14, 29, 10, 10, 22, 22, 20, 23, 26, 7, 19, 19, 12, 12, 20, 29, 19, 0, 14, 14, 21, 21, 26, 20, 24, 1, 28, 28, 22, 22, 18, 27, 27, 3, 24, 24, 22, 22, 18, 27, 27, 3, 24, 24, 21, 21, 26, 20, 24, 1, 28, 28, 12, 12, 20, 29, 19, 0, 14, 14, 22, 22, 20, 23, 26, 7, 19, 19, 21, 21, 28, 21, 14, 29, 10, 10, 9, 9, 7, 20, 20, 13, 16, 16, 9, 9, 7, 20, 20, 13, 16, 16, 3, 3, 16, 28, 23, 3, 15, 15, 21, 21, 8, 27, 14, 21, 12, 12, 30, 30, 23, 17, 4, 13, 1, 1, 18, 18, 26, 5, 15, 14, 12, 12, 18, 18, 26, 5, 15, 14, 12, 12, 30, 30, 23, 17, 4, 13, 1, 1, 21, 21, 8, 27, 14, 21, 12, 12, 3, 3, 16, 28, 23, 3, 15, 15, 9, 9, 7, 20, 20, 13, 16, 16, 11, 11, 14, 24, 8, 16, 14, 14, 11, 11, 14, 24, 8, 16, 14, 14, 29, 29, 24, 28, 25, 9, 7, 7, 15, 15, 8, 13, 20, 28, 18, 18, 25, 25, 3, 11, 30, 4, 13, 13, 2, 2, 3, 27, 30, 19, 4, 4, 2, 2, 3, 27, 30, 19, 4, 4, 25, 25, 3, 11, 30, 4, 13, 13, 15, 15, 8, 13, 20, 28, 18, 18, 29, 29, 24, 28, 25, 9, 7, 7, 11, 11, 14, 24, 8, 16, 14, 14, 11, 11, 14, 24, 8, 16, 14, 14, 11, 11, 14, 24, 8, 16, 14, 14, 29, 29, 24, 28, 25, 9, 7, 7, 15, 15, 8, 13, 20, 28, 18, 18, 25, 25, 3, 11, 30, 4, 13, 13, 2, 2, 3, 27, 30, 19, 4, 4, 2, 2, 3, 27, 30, 19, 4, 4, 25, 25, 3, 11, 30, 4, 13, 13, 15, 15, 8, 13, 20, 28, 18, 18, 29, 29, 24, 28, 25, 9, 7, 7, 11, 11, 14, 24, 8, 16, 14, 14, 9, 9, 7, 20, 20, 13, 16, 16, 9, 9, 7, 20, 20, 13, 16, 16, 3, 3, 16, 28, 23, 3, 15, 15, 21, 21, 8, 27, 14, 21, 12, 12, 30, 30, 23, 17, 4, 13, 1, 1, 18, 18, 26, 5, 15, 14, 12, 12, 18, 18, 26, 5, 15, 14, 12, 12, 30, 30, 23, 17, 4, 13, 1, 1, 21, 21, 8, 27, 14, 21, 12, 12, 3, 3, 16, 28, 23, 3, 15, 15, 9, 9, 7, 20, 20, 13, 16, 16, 21, 21, 28, 21, 14, 29, 10, 10, 21, 21, 28, 21, 14, 29, 10, 10, 22, 22, 20, 23, 26, 7, 19, 19, 12, 12, 20, 29, 19, 0, 14, 14, 21, 21, 26, 20, 24, 1, 28, 28, 22, 22, 18, 27, 27, 3, 24, 24, 22, 22, 18, 27, 27, 3, 24, 24, 21, 21, 26, 20, 24, 1, 28, 28, 12, 12, 20, 29, 19, 0, 14, 14, 22, 22, 20, 23, 26, 7, 19, 19, 21, 21, 28, 21, 14, 29, 10, 10, 23, 23, 6, 22, 18, 6, 24, 24, 23, 23, 6, 22, 18, 6, 24, 24, 4, 4, 18, 13, 8, 17, 14, 14, 6, 6, 29, 2, 0, 15, 25, 25, 20, 20, 23, 15, 20, 10, 8, 8, 15, 15, 1, 2, 23, 5, 23, 23, 15, 15, 1, 2, 23, 5, 23, 23, 20, 20, 23, 15, 20, 10, 8, 8, 6, 6, 29, 2, 0, 15, 25, 25, 4, 4, 18, 13, 8, 17, 14, 14, 23, 23, 6, 22, 18, 6, 24, 24, 23, 23, 6, 22, 18, 6, 24, 24, 23, 23, 6, 22, 18, 6, 24, 24, 4, 4, 18, 13, 8, 17, 14, 14, 6, 6, 29, 2, 0, 15, 25, 25, 20, 20, 23, 15, 20, 10, 8, 8, 15, 15, 1, 2, 23, 5, 23, 23, 15, 15, 1, 2, 23, 5, 23, 23, 20, 20, 23, 15, 20, 10, 8, 8, 6, 6, 29, 2, 0, 15, 25, 25, 4, 4, 18, 13, 8, 17, 14, 14, 23, 23, 6, 22, 18, 6, 24, 24, 21, 21, 28, 21, 14, 29, 10, 10, 21, 21, 28, 21, 14, 29, 10, 10, 22, 22, 20, 23, 26, 7, 19, 19, 12, 12, 20, 29, 19, 0, 14, 14, 21, 21, 26, 20, 24, 1, 28, 28, 22, 22, 18, 27, 27, 3, 24, 24, 22, 22, 18, 27, 27, 3, 24, 24, 21, 21, 26, 20, 24, 1, 28, 28, 12, 12, 20, 29, 19, 0, 14, 14, 22, 22, 20, 23, 26, 7, 19, 19, 21, 21, 28, 21, 14, 29, 10, 10, 0, 0, 14, 12, 15, 6, 18, 18, 0, 0, 14, 12, 15, 6, 18, 18, 2, 2, 9, 11, 28, 2, 23, 23, 6, 6, 17, 12, 14, 23, 12, 12, 4, 4, 4, 2, 26, 19, 29, 29, 21, 21, 1, 20, 23, 22, 15, 15, 21, 21, 1, 20, 23, 22, 15, 15, 4, 4, 4, 2, 26, 19, 29, 29, 6, 6, 17, 12, 14, 23, 12, 12, 2, 2, 9, 11, 28, 2, 23, 23, 0, 0, 14, 12, 15, 6, 18, 18, 16, 16, 14, 9, 19, 6, 27, 27, 16, 16, 14, 9, 19, 6, 27, 27, 29, 29, 22, 13, 15, 17, 2, 2, 13, 13, 16, 5, 3, 24, 11, 11, 16, 16, 28, 18, 9, 30, 11, 11, 1, 1, 21, 3, 9, 25, 20, 20, 1, 1, 21, 3, 9, 25, 20, 20, 16, 16, 28, 18, 9, 30, 11, 11, 13, 13, 16, 5, 3, 24, 11, 11, 29, 29, 22, 13, 15, 17, 2, 2, 16, 16, 14, 9, 19, 6, 27, 27, 4, 4, 2, 1, 5, 3, 19, 19, 4, 4, 2, 1, 5, 3, 19, 19, 15, 15, 30, 28, 30, 7, 13, 13, 8, 8, 18, 19, 24, 21, 8, 8, 13, 13, 16, 0, 1, 12, 3, 3, 22, 22, 7, 3, 5, 7, 7, 7, 22, 22, 7, 3, 5, 7, 7, 7, 13, 13, 16, 0, 1, 12, 3, 3, 8, 8, 18, 19, 24, 21, 8, 8, 15, 15, 30, 28, 30, 7, 13, 13, 4, 4, 2, 1, 5, 3, 19, 19, 18, 18, 22, 3, 10, 1, 13, 13, 18, 18, 22, 3, 10, 1, 13, 13, 23, 23, 22, 27, 23, 26, 21, 21, 14, 14, 7, 20, 9, 3, 13, 13, 26, 26, 4, 18, 12, 15, 4, 4, 29, 29, 8, 18, 13, 1, 17, 17, 29, 29, 8, 18, 13, 1, 17, 17, 26, 26, 4, 18, 12, 15, 4, 4, 14, 14, 7, 20, 9, 3, 13, 13, 23, 23, 22, 27, 23, 26, 21, 21, 18, 18, 22, 3, 10, 1, 13, 13, 18, 18, 22, 3, 10, 1, 13, 13, 18, 18, 22, 3, 10, 1, 13, 13, 23, 23, 22, 27, 23, 26, 21, 21, 14, 14, 7, 20, 9, 3, 13, 13, 26, 26, 4, 18, 12, 15, 4, 4, 29, 29, 8, 18, 13, 1, 17, 17, 29, 29, 8, 18, 13, 1, 17, 17, 26, 26, 4, 18, 12, 15, 4, 4, 14, 14, 7, 20, 9, 3, 13, 13, 23, 23, 22, 27, 23, 26, 21, 21, 18, 18, 22, 3, 10, 1, 13, 13, 4, 4, 2, 1, 5, 3, 19, 19, 4, 4, 2, 1, 5, 3, 19, 19, 15, 15, 30, 28, 30, 7, 13, 13, 8, 8, 18, 19, 24, 21, 8, 8, 13, 13, 16, 0, 1, 12, 3, 3, 22, 22, 7, 3, 5, 7, 7, 7, 22, 22, 7, 3, 5, 7, 7, 7, 13, 13, 16, 0, 1, 12, 3, 3, 8, 8, 18, 19, 24, 21, 8, 8, 15, 15, 30, 28, 30, 7, 13, 13, 4, 4, 2, 1, 5, 3, 19, 19, 16, 16, 14, 9, 19, 6, 27, 27, 16, 16, 14, 9, 19, 6, 27, 27, 29, 29, 22, 13, 15, 17, 2, 2, 13, 13, 16, 5, 3, 24, 11, 11, 16, 16, 28, 18, 9, 30, 11, 11, 1, 1, 21, 3, 9, 25, 20, 20, 1, 1, 21, 3, 9, 25, 20, 20, 16, 16, 28, 18, 9, 30, 11, 11, 13, 13, 16, 5, 3, 24, 11, 11, 29, 29, 22, 13, 15, 17, 2, 2, 16, 16, 14, 9, 19, 6, 27, 27, 0, 0, 14, 12, 15, 6, 18, 18, 0, 0, 14, 12, 15, 6, 18, 18, 2, 2, 9, 11, 28, 2, 23, 23, 6, 6, 17, 12, 14, 23, 12, 12, 4, 4, 4, 2, 26, 19, 29, 29, 21, 21, 1, 20, 23, 22, 15, 15, 21, 21, 1, 20, 23, 22, 15, 15, 4, 4, 4, 2, 26, 19, 29, 29, 6, 6, 17, 12, 14, 23, 12, 12, 2, 2, 9, 11, 28, 2, 23, 23, 0, 0, 14, 12, 15, 6, 18, 18, 0, 0, 14, 12, 15, 6, 18, 18, 0, 0, 14, 12, 15, 6, 18, 18, 2, 2, 9, 11, 28, 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25, 3, 11, 30, 4, 13, 13, 2, 2, 3, 27, 30, 19, 4, 4, 2, 2, 3, 27, 30, 19, 4, 4, 25, 25, 3, 11, 30, 4, 13, 13, 15, 15, 8, 13, 20, 28, 18, 18, 29, 29, 24, 28, 25, 9, 7, 7, 11, 11, 14, 24, 8, 16, 14, 14, 9, 9, 7, 20, 20, 13, 16, 16, 9, 9, 7, 20, 20, 13, 16, 16, 3, 3, 16, 28, 23, 3, 15, 15, 21, 21, 8, 27, 14, 21, 12, 12, 30, 30, 23, 17, 4, 13, 1, 1, 18, 18, 26, 5, 15, 14, 12, 12, 18, 18, 26, 5, 15, 14, 12, 12, 30, 30, 23, 17, 4, 13, 1, 1, 21, 21, 8, 27, 14, 21, 12, 12, 3, 3, 16, 28, 23, 3, 15, 15, 9, 9, 7, 20, 20, 13, 16, 16, 21, 21, 28, 21, 14, 29, 10, 10, 21, 21, 28, 21, 14, 29, 10, 10, 22, 22, 20, 23, 26, 7, 19, 19, 12, 12, 20, 29, 19, 0, 14, 14, 21, 21, 26, 20, 24, 1, 28, 28, 22, 22, 18, 27, 27, 3, 24, 24, 22, 22, 18, 27, 27, 3, 24, 24, 21, 21, 26, 20, 24, 1, 28, 28, 12, 12, 20, 29, 19, 0, 14, 14, 22, 22, 20, 23, 26, 7, 19, 19, 21, 21, 28, 21, 14, 29, 10, 10, 23, 23, 6, 22, 18, 6, 24, 24, 23, 23, 6, 22, 18, 6, 24, 24, 4, 4, 18, 13, 8, 17, 14, 14, 6, 6, 29, 2, 0, 15, 25, 25, 20, 20, 23, 15, 20, 10, 8, 8, 15, 15, 1, 2, 23, 5, 23, 23, 15, 15, 1, 2, 23, 5, 23, 23, 20, 20, 23, 15, 20, 10, 8, 8, 6, 6, 29, 2, 0, 15, 25, 25, 4, 4, 18, 13, 8, 17, 14, 14, 23, 23, 6, 22, 18, 6, 24, 24, 23, 23, 6, 22, 18, 6, 24, 24, 23, 23, 6, 22, 18, 6, 24, 24, 4, 4, 18, 13, 8, 17, 14, 14, 6, 6, 29, 2, 0, 15, 25, 25, 20, 20, 23, 15, 20, 10, 8, 8, 15, 15, 1, 2, 23, 5, 23, 23, 15, 15, 1, 2, 23, 5, 23, 23, 20, 20, 23, 15, 20, 10, 8, 8, 6, 6, 29, 2, 0, 15, 25, 25, 4, 4, 18, 13, 8, 17, 14, 14, 23, 23, 6, 22, 18, 6, 24, 24, 21, 21, 28, 21, 14, 29, 10, 10, 21, 21, 28, 21, 14, 29, 10, 10, 22, 22, 20, 23, 26, 7, 19, 19, 12, 12, 20, 29, 19, 0, 14, 14, 21, 21, 26, 20, 24, 1, 28, 28, 22, 22, 18, 27, 27, 3, 24, 24, 22, 22, 18, 27, 27, 3, 24, 24, 21, 21, 26, 20, 24, 1, 28, 28, 12, 12, 20, 29, 19, 0, 14, 14, 22, 22, 20, 23, 26, 7, 19, 19, 21, 21, 28, 21, 14, 29, 10, 10, 0, 0, 14, 12, 15, 6, 18, 18, 0, 0, 14, 12, 15, 6, 18, 18, 2, 2, 9, 11, 28, 2, 23, 23, 6, 6, 17, 12, 14, 23, 12, 12, 4, 4, 4, 2, 26, 19, 29, 29, 21, 21, 1, 20, 23, 22, 15, 15, 21, 21, 1, 20, 23, 22, 15, 15, 4, 4, 4, 2, 26, 19, 29, 29, 6, 6, 17, 12, 14, 23, 12, 12, 2, 2, 9, 11, 28, 2, 23, 23, 0, 0, 14, 12, 15, 6, 18, 18, 16, 16, 14, 9, 19, 6, 27, 27, 16, 16, 14, 9, 19, 6, 27, 27, 29, 29, 22, 13, 15, 17, 2, 2, 13, 13, 16, 5, 3, 24, 11, 11, 16, 16, 28, 18, 9, 30, 11, 11, 1, 1, 21, 3, 9, 25, 20, 20, 1, 1, 21, 3, 9, 25, 20, 20, 16, 16, 28, 18, 9, 30, 11, 11, 13, 13, 16, 5, 3, 24, 11, 11, 29, 29, 22, 13, 15, 17, 2, 2, 16, 16, 14, 9, 19, 6, 27, 27, 4, 4, 2, 1, 5, 3, 19, 19, 4, 4, 2, 1, 5, 3, 19, 19, 15, 15, 30, 28, 30, 7, 13, 13, 8, 8, 18, 19, 24, 21, 8, 8, 13, 13, 16, 0, 1, 12, 3, 3, 22, 22, 7, 3, 5, 7, 7, 7, 22, 22, 7, 3, 5, 7, 7, 7, 13, 13, 16, 0, 1, 12, 3, 3, 8, 8, 18, 19, 24, 21, 8, 8, 15, 15, 30, 28, 30, 7, 13, 13, 4, 4, 2, 1, 5, 3, 19, 19, 18, 18, 22, 3, 10, 1, 13, 13, 18, 18, 22, 3, 10, 1, 13, 13, 23, 23, 22, 27, 23, 26, 21, 21, 14, 14, 7, 20, 9, 3, 13, 13, 26, 26, 4, 18, 12, 15, 4, 4, 29, 29, 8, 18, 13, 1, 17, 17, 29, 29, 8, 18, 13, 1, 17, 17, 26, 26, 4, 18, 12, 15, 4, 4, 14, 14, 7, 20, 9, 3, 13, 13, 23, 23, 22, 27, 23, 26, 21, 21, 18, 18, 22, 3, 10, 1, 13, 13, 18, 18, 22, 3, 10, 1, 13, 13, 18, 18, 22, 3, 10, 1, 13, 13, 23, 23, 22, 27, 23, 26, 21, 21, 14, 14, 7, 20, 9, 3, 13, 13, 26, 26, 4, 18, 12, 15, 4, 4, 29, 29, 8, 18, 13, 1, 17, 17, 29, 29, 8, 18, 13, 1, 17, 17, 26, 26, 4, 18, 12, 15, 4, 4, 14, 14, 7, 20, 9, 3, 13, 13, 23, 23, 22, 27, 23, 26, 21, 21, 18, 18, 22, 3, 10, 1, 13, 13, 4, 4, 2, 1, 5, 3, 19, 19, 4, 4, 2, 1, 5, 3, 19, 19, 15, 15, 30, 28, 30, 7, 13, 13, 8, 8, 18, 19, 24, 21, 8, 8, 13, 13, 16, 0, 1, 12, 3, 3, 22, 22, 7, 3, 5, 7, 7, 7, 22, 22, 7, 3, 5, 7, 7, 7, 13, 13, 16, 0, 1, 12, 3, 3, 8, 8, 18, 19, 24, 21, 8, 8, 15, 15, 30, 28, 30, 7, 13, 13, 4, 4, 2, 1, 5, 3, 19, 19, 16, 16, 14, 9, 19, 6, 27, 27, 16, 16, 14, 9, 19, 6, 27, 27, 29, 29, 22, 13, 15, 17, 2, 2, 13, 13, 16, 5, 3, 24, 11, 11, 16, 16, 28, 18, 9, 30, 11, 11, 1, 1, 21, 3, 9, 25, 20, 20, 1, 1, 21, 3, 9, 25, 20, 20, 16, 16, 28, 18, 9, 30, 11, 11, 13, 13, 16, 5, 3, 24, 11, 11, 29, 29, 22, 13, 15, 17, 2, 2, 16, 16, 14, 9, 19, 6, 27, 27, 0, 0, 14, 12, 15, 6, 18, 18, 0, 0, 14, 12, 15, 6, 18, 18, 2, 2, 9, 11, 28, 2, 23, 23, 6, 6, 17, 12, 14, 23, 12, 12, 4, 4, 4, 2, 26, 19, 29, 29, 21, 21, 1, 20, 23, 22, 15, 15, 21, 21, 1, 20, 23, 22, 15, 15, 4, 4, 4, 2, 26, 19, 29, 29, 6, 6, 17, 12, 14, 23, 12, 12, 2, 2, 9, 11, 28, 2, 23, 23, 0, 0, 14, 12, 15, 6, 18, 18, 0, 0, 14, 12, 15, 6, 18, 18, 0, 0, 14, 12, 15, 6, 18, 18, 2, 2, 9, 11, 28, 2, 23, 23, 6, 6, 17, 12, 14, 23, 12, 12, 4, 4, 4, 2, 26, 19, 29, 29, 21, 21, 1, 20, 23, 22, 15, 15, 21, 21, 1, 20, 23, 22, 15, 15, 4, 4, 4, 2, 26, 19, 29, 29, 6, 6, 17, 12, 14, 23, 12, 12, 2, 2, 9, 11, 28, 2, 23, 23, 0, 0, 14, 12, 15, 6, 18, 18, 16, 16, 14, 9, 19, 6, 27, 27, 16, 16, 14, 9, 19, 6, 27, 27, 29, 29, 22, 13, 15, 17, 2, 2, 13, 13, 16, 5, 3, 24, 11, 11, 16, 16, 28, 18, 9, 30, 11, 11, 1, 1, 21, 3, 9, 25, 20, 20, 1, 1, 21, 3, 9, 25, 20, 20, 16, 16, 28, 18, 9, 30, 11, 11, 13, 13, 16, 5, 3, 24, 11, 11, 29, 29, 22, 13, 15, 17, 2, 2, 16, 16, 14, 9, 19, 6, 27, 27, 7, 7, 26, 3, 16, 26, 7, 7, 7, 7, 26, 3, 16, 26, 7, 7, 6, 6, 26, 13, 22, 1, 11, 11, 5, 5, 20, 2, 29, 1, 22, 22, 1, 1, 8, 24, 5, 6, 21, 21, 12, 12, 1, 30, 5, 1, 10, 10, 12, 12, 1, 30, 5, 1, 10, 10, 1, 1, 8, 24, 5, 6, 21, 21, 5, 5, 20, 2, 29, 1, 22, 22, 6, 6, 26, 13, 22, 1, 11, 11, 7, 7, 26, 3, 16, 26, 7, 7, 22, 22, 15, 7, 10, 21, 5, 5, 22, 22, 15, 7, 10, 21, 5, 5, 27, 27, 8, 27, 9, 29, 21, 21, 15, 15, 16, 20, 18, 9, 6, 6, 15, 15, 28, 19, 2, 25, 22, 22, 27, 27, 6, 22, 2, 20, 8, 8, 27, 27, 6, 22, 2, 20, 8, 8, 15, 15, 28, 19, 2, 25, 22, 22, 15, 15, 16, 20, 18, 9, 6, 6, 27, 27, 8, 27, 9, 29, 21, 21, 22, 22, 15, 7, 10, 21, 5, 5, 10, 10, 4, 15, 30, 20, 5, 5, 10, 10, 4, 15, 30, 20, 5, 5, 27, 27, 24, 22, 27, 23, 24, 24, 11, 11, 29, 29, 5, 23, 21, 21, 14, 14, 16, 15, 28, 15, 25, 25, 11, 11, 26, 27, 14, 17, 28, 28, 11, 11, 26, 27, 14, 17, 28, 28, 14, 14, 16, 15, 28, 15, 25, 25, 11, 11, 29, 29, 5, 23, 21, 21, 27, 27, 24, 22, 27, 23, 24, 24, 10, 10, 4, 15, 30, 20, 5, 5, 29, 29, 28, 2, 3, 25, 22, 22, 29, 29, 28, 2, 3, 25, 22, 22, 20, 20, 9, 18, 18, 17, 5, 5, 13, 13, 12, 22, 30, 28, 16, 16, 13, 13, 8, 1, 1, 14, 10, 10, 11, 11, 27, 16, 17, 7, 1, 1, 11, 11, 27, 16, 17, 7, 1, 1, 13, 13, 8, 1, 1, 14, 10, 10, 13, 13, 12, 22, 30, 28, 16, 16, 20, 20, 9, 18, 18, 17, 5, 5, 29, 29, 28, 2, 3, 25, 22, 22, 29, 29, 28, 2, 3, 25, 22, 22, 29, 29, 28, 2, 3, 25, 22, 22, 20, 20, 9, 18, 18, 17, 5, 5, 13, 13, 12, 22, 30, 28, 16, 16, 13, 13, 8, 1, 1, 14, 10, 10, 11, 11, 27, 16, 17, 7, 1, 1, 11, 11, 27, 16, 17, 7, 1, 1, 13, 13, 8, 1, 1, 14, 10, 10, 13, 13, 12, 22, 30, 28, 16, 16, 20, 20, 9, 18, 18, 17, 5, 5, 29, 29, 28, 2, 3, 25, 22, 22, 10, 10, 4, 15, 30, 20, 5, 5, 10, 10, 4, 15, 30, 20, 5, 5, 27, 27, 24, 22, 27, 23, 24, 24, 11, 11, 29, 29, 5, 23, 21, 21, 14, 14, 16, 15, 28, 15, 25, 25, 11, 11, 26, 27, 14, 17, 28, 28, 11, 11, 26, 27, 14, 17, 28, 28, 14, 14, 16, 15, 28, 15, 25, 25, 11, 11, 29, 29, 5, 23, 21, 21, 27, 27, 24, 22, 27, 23, 24, 24, 10, 10, 4, 15, 30, 20, 5, 5, 22, 22, 15, 7, 10, 21, 5, 5, 22, 22, 15, 7, 10, 21, 5, 5, 27, 27, 8, 27, 9, 29, 21, 21, 15, 15, 16, 20, 18, 9, 6, 6, 15, 15, 28, 19, 2, 25, 22, 22, 27, 27, 6, 22, 2, 20, 8, 8, 27, 27, 6, 22, 2, 20, 8, 8, 15, 15, 28, 19, 2, 25, 22, 22, 15, 15, 16, 20, 18, 9, 6, 6, 27, 27, 8, 27, 9, 29, 21, 21, 22, 22, 15, 7, 10, 21, 5, 5, 7, 7, 26, 3, 16, 26, 7, 7, 7, 7, 26, 3, 16, 26, 7, 7, 6, 6, 26, 13, 22, 1, 11, 11, 5, 5, 20, 2, 29, 1, 22, 22, 1, 1, 8, 24, 5, 6, 21, 21, 12, 12, 1, 30, 5, 1, 10, 10, 12, 12, 1, 30, 5, 1, 10, 10, 1, 1, 8, 24, 5, 6, 21, 21, 5, 5, 20, 2, 29, 1, 22, 22, 6, 6, 26, 13, 22, 1, 11, 11, 7, 7, 26, 3, 16, 26, 7, 7, 7, 7, 26, 3, 16, 26, 7, 7, 7, 7, 26, 3, 16, 26, 7, 7, 6, 6, 26, 13, 22, 1, 11, 11, 5, 5, 20, 2, 29, 1, 22, 22, 1, 1, 8, 24, 5, 6, 21, 21, 12, 12, 1, 30, 5, 1, 10, 10, 12, 12, 1, 30, 5, 1, 10, 10, 1, 1, 8, 24, 5, 6, 21, 21, 5, 5, 20, 2, 29, 1, 22, 22, 6, 6, 26, 13, 22, 1, 11, 11, 7, 7, 26, 3, 16, 26, 7, 7, 22, 22, 15, 7, 10, 21, 5, 5, 22, 22, 15, 7, 10, 21, 5, 5, 27, 27, 8, 27, 9, 29, 21, 21, 15, 15, 16, 20, 18, 9, 6, 6, 15, 15, 28, 19, 2, 25, 22, 22, 27, 27, 6, 22, 2, 20, 8, 8, 27, 27, 6, 22, 2, 20, 8, 8, 15, 15, 28, 19, 2, 25, 22, 22, 15, 15, 16, 20, 18, 9, 6, 6, 27, 27, 8, 27, 9, 29, 21, 21, 22, 22, 15, 7, 10, 21, 5, 5}),
+ .dimensions = {9, 10, 11, 8},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_three_symmetric_int32_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_three_symmetric_int32_all_tensors_as_inputs", get_test_model_three_symmetric_int32_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad
+
diff --git a/runtime/test/generated/spec_AIDL_V3/mirror_pad_tensorflow.example.cpp b/runtime/test/generated/spec_AIDL_V3/mirror_pad_tensorflow.example.cpp
new file mode 100644
index 0000000..a4e4fe5
--- /dev/null
+++ b/runtime/test/generated/spec_AIDL_V3/mirror_pad_tensorflow.example.cpp
@@ -0,0 +1,4440 @@
+// Generated from mirror_pad_tensorflow.mod.py
+// DO NOT EDIT
+// clang-format off
+#include "TestHarness.h"
+using namespace test_helper;
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary = TestModelManager::get().add("mirror_pad_tensorflow_summary", get_test_model_summary());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // t_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // placeholder
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // param3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_summary_all_inputs_as_internal", get_test_model_summary_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_summary_all_tensors_as_inputs", get_test_model_summary_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // t_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // placeholder1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // param4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_summary_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_summary_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_float16() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_float16 = TestModelManager::get().add("mirror_pad_tensorflow_summary_float16", get_test_model_summary_float16());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_float16_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // t_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // placeholder2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // param5
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_float16_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_summary_float16_all_inputs_as_internal", get_test_model_summary_float16_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_float16_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_float16_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_summary_float16_all_tensors_as_inputs", get_test_model_summary_float16_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_float16_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 2.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f, 5.0f, 4.0f, 4.0f, 5.0f, 6.0f, 6.0f, 5.0f}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // t_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // placeholder3
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // param6
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_float16_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_summary_float16_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_summary_float16_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_quant8_asymm() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10, 12, 14, 16}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({8, 6, 6, 8, 10, 10, 8, 8, 6, 6, 8, 10, 10, 8, 14, 12, 12, 14, 16, 16, 14, 14, 12, 12, 14, 16, 16, 14}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_quant8_asymm = TestModelManager::get().add("mirror_pad_tensorflow_summary_quant8_asymm", get_test_model_summary_quant8_asymm());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_quant8_asymm_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({8, 6, 6, 8, 10, 10, 8, 8, 6, 6, 8, 10, 10, 8, 14, 12, 12, 14, 16, 16, 14, 14, 12, 12, 14, 16, 16, 14}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // t_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10, 12, 14, 16}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // placeholder4
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({4}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // param7
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_quant8_asymm_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_summary_quant8_asymm_all_inputs_as_internal", get_test_model_summary_quant8_asymm_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_quant8_asymm_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10, 12, 14, 16}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({8, 6, 6, 8, 10, 10, 8, 8, 6, 6, 8, 10, 10, 8, 14, 12, 12, 14, 16, 16, 14, 14, 12, 12, 14, 16, 16, 14}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_quant8_asymm_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_summary_quant8_asymm_all_tensors_as_inputs", get_test_model_summary_quant8_asymm_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({8, 6, 6, 8, 10, 10, 8, 8, 6, 6, 8, 10, 10, 8, 14, 12, 12, 14, 16, 16, 14, 14, 12, 12, 14, 16, 16, 14}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // t_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10, 12, 14, 16}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // placeholder5
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({4}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // param8
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_summary_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_summary_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_quant8_asymm_signed() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3, 7, 11, 15}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-1, -5, -5, -1, 3, 3, -1, -1, -5, -5, -1, 3, 3, -1, 11, 7, 7, 11, 15, 15, 11, 11, 7, 7, 11, 15, 15, 11}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_quant8_asymm_signed = TestModelManager::get().add("mirror_pad_tensorflow_summary_quant8_asymm_signed", get_test_model_summary_quant8_asymm_signed());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_quant8_asymm_signed_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-1, -5, -5, -1, 3, 3, -1, -1, -5, -5, -1, 3, 3, -1, 11, 7, 7, 11, 15, 15, 11, 11, 7, 7, 11, 15, 15, 11}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // t_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3, 7, 11, 15}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // placeholder6
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-9}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // param9
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_quant8_asymm_signed_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_summary_quant8_asymm_signed_all_inputs_as_internal", get_test_model_summary_quant8_asymm_signed_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_quant8_asymm_signed_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3, 7, 11, 15}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-1, -5, -5, -1, 3, 3, -1, -1, -5, -5, -1, 3, 3, -1, 11, 7, 7, 11, 15, 15, 11, 11, 7, 7, 11, 15, 15, 11}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_quant8_asymm_signed_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_summary_quant8_asymm_signed_all_tensors_as_inputs", get_test_model_summary_quant8_asymm_signed_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-1, -5, -5, -1, 3, 3, -1, -1, -5, -5, -1, 3, 3, -1, 11, 7, 7, 11, 15, 15, 11, 11, 7, 7, 11, 15, 15, 11}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // t_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3, 7, 11, 15}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // placeholder7
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-9}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // param10
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_summary_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_summary_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_int32() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 2, 3, 4, 5, 6}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({2, 1, 1, 2, 3, 3, 2, 2, 1, 1, 2, 3, 3, 2, 5, 4, 4, 5, 6, 6, 5, 5, 4, 4, 5, 6, 6, 5}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_int32 = TestModelManager::get().add("mirror_pad_tensorflow_summary_int32", get_test_model_summary_int32());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_summary_int32_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 2, 3, 4, 5, 6}),
+ .dimensions = {2, 3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // paddings
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 1, 2, 2}),
+ .dimensions = {2, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({2, 1, 1, 2, 3, 3, 2, 2, 1, 1, 2, 3, 3, 2, 5, 4, 4, 5, 6, 6, 5, 5, 4, 4, 5, 6, 6, 5}),
+ .dimensions = {4, 7},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_summary_int32_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_summary_int32_all_tensors_as_inputs", get_test_model_summary_int32_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f, 2.0f, 1.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect", get_test_model_mode_reflect());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f, 2.0f, 1.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // t1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // placeholder8
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // param11
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_all_inputs_as_internal", get_test_model_mode_reflect_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f, 2.0f, 1.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_all_tensors_as_inputs", get_test_model_mode_reflect_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f, 2.0f, 1.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // t1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // placeholder9
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // param12
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_mode_reflect_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_float16() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f, 2.0f, 1.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_float16 = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_float16", get_test_model_mode_reflect_float16());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_float16_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f, 2.0f, 1.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // t1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // placeholder10
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // param13
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_float16_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_float16_all_inputs_as_internal", get_test_model_mode_reflect_float16_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_float16_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f, 2.0f, 1.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_float16_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_float16_all_tensors_as_inputs", get_test_model_mode_reflect_float16_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_float16_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f, 2.0f, 1.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // t1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // placeholder11
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // param14
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_float16_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_float16_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_mode_reflect_float16_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_quant8_asymm() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10, 8, 6}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_quant8_asymm = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_quant8_asymm", get_test_model_mode_reflect_quant8_asymm());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_quant8_asymm_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10, 8, 6}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // t1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // placeholder12
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({4}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // param15
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_quant8_asymm_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_quant8_asymm_all_inputs_as_internal", get_test_model_mode_reflect_quant8_asymm_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_quant8_asymm_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10, 8, 6}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_quant8_asymm_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_quant8_asymm_all_tensors_as_inputs", get_test_model_mode_reflect_quant8_asymm_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10, 8, 6}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // t1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // placeholder13
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({4}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // param16
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_mode_reflect_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_quant8_asymm_signed() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3, -1, -5}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_quant8_asymm_signed = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_quant8_asymm_signed", get_test_model_mode_reflect_quant8_asymm_signed());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_quant8_asymm_signed_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3, -1, -5}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // t1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // placeholder14
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-9}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // param17
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_quant8_asymm_signed_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_quant8_asymm_signed_all_inputs_as_internal", get_test_model_mode_reflect_quant8_asymm_signed_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_quant8_asymm_signed_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3, -1, -5}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_quant8_asymm_signed_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_quant8_asymm_signed_all_tensors_as_inputs", get_test_model_mode_reflect_quant8_asymm_signed_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3, -1, -5}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // t1_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // placeholder15
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-9}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // param18
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_mode_reflect_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_int32() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 2, 3}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 2, 3, 2, 1}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_int32 = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_int32", get_test_model_mode_reflect_int32());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_reflect_int32_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 2, 3}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // paddings1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output1
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 2, 3, 2, 1}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_reflect_int32_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_mode_reflect_int32_all_tensors_as_inputs", get_test_model_mode_reflect_int32_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f, 3.0f, 2.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric", get_test_model_mode_symmetric());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f, 3.0f, 2.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // t2_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // placeholder16
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // param19
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_all_inputs_as_internal", get_test_model_mode_symmetric_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f, 3.0f, 2.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_all_tensors_as_inputs", get_test_model_mode_symmetric_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f, 3.0f, 2.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // t2_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // placeholder17
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<float>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT32,
+ .zeroPoint = 0
+ }, { // param20
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_mode_symmetric_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_float16() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f, 3.0f, 2.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_float16 = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_float16", get_test_model_mode_symmetric_float16());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_float16_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f, 3.0f, 2.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // t2_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // placeholder18
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // param21
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_float16_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_float16_all_inputs_as_internal", get_test_model_mode_symmetric_float16_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_float16_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f, 3.0f, 2.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_float16_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_float16_all_tensors_as_inputs", get_test_model_mode_symmetric_float16_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_float16_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f, 3.0f, 2.0f}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // t2_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({1.0f, 2.0f, 3.0f}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // placeholder19
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<_Float16>({0.0f}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_FLOAT16,
+ .zeroPoint = 0
+ }, { // param22
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_float16_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_float16_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_mode_symmetric_float16_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_quant8_asymm() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10, 10, 8}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_quant8_asymm = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_quant8_asymm", get_test_model_mode_symmetric_quant8_asymm());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_quant8_asymm_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10, 10, 8}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // t2_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // placeholder20
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({4}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // param23
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_quant8_asymm_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_quant8_asymm_all_inputs_as_internal", get_test_model_mode_symmetric_quant8_asymm_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_quant8_asymm_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10, 10, 8}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_quant8_asymm_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_quant8_asymm_all_tensors_as_inputs", get_test_model_mode_symmetric_quant8_asymm_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10, 10, 8}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // t2_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({6, 8, 10}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // placeholder21
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<uint8_t>({4}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.5f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+ .zeroPoint = 4
+ }, { // param24
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_mode_symmetric_quant8_asymm_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_quant8_asymm_signed() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3, 3, -1}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_quant8_asymm_signed = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_quant8_asymm_signed", get_test_model_mode_symmetric_quant8_asymm_signed());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_quant8_asymm_signed_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {4},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3, 3, -1}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // t2_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // placeholder22
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-9}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // param25
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_quant8_asymm_signed_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_quant8_asymm_signed_all_inputs_as_internal", get_test_model_mode_symmetric_quant8_asymm_signed_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_quant8_asymm_signed_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3, 3, -1}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_quant8_asymm_signed_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_quant8_asymm_signed_all_tensors_as_inputs", get_test_model_mode_symmetric_quant8_asymm_signed_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {1, 4},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::TEMPORARY_VARIABLE,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3, 3, -1}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // t2_new
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-5, -1, 3}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // placeholder23
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int8_t>({-9}),
+ .dimensions = {1},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.25f,
+ .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+ .zeroPoint = -9
+ }, { // param26
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {4, 5, 6},
+ .outputs = {0},
+ .type = TestOperationType::ADD
+ }, {
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal", get_test_model_mode_symmetric_quant8_asymm_signed_all_tensors_as_inputs_all_inputs_as_internal());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_int32() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 2, 3}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 2, 3, 3, 2}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_int32 = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_int32", get_test_model_mode_symmetric_int32());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
+namespace generated_tests::mirror_pad_tensorflow {
+
+const TestModel& get_test_model_mode_symmetric_int32_all_tensors_as_inputs() {
+ static TestModel model = {
+ .expectFailure = false,
+ .expectedMultinomialDistributionTolerance = 0,
+ .isRelaxed = false,
+ .main = {
+ .inputIndexes = {0, 1},
+ .operands = {{ // t2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 2, 3}),
+ .dimensions = {3},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // paddings2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({0, 2}),
+ .dimensions = {1, 2},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }, { // param2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1}),
+ .dimensions = {},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .type = TestOperandType::INT32,
+ .zeroPoint = 0
+ }, { // output2
+ .channelQuant = {},
+ .data = TestBuffer::createFromVector<int32_t>({1, 2, 3, 3, 2}),
+ .dimensions = {5},
+ .isIgnored = false,
+ .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .type = TestOperandType::TENSOR_INT32,
+ .zeroPoint = 0
+ }},
+ .operations = {{
+ .inputs = {0, 1, 2},
+ .outputs = {3},
+ .type = TestOperationType::MIRROR_PAD
+ }},
+ .outputIndexes = {3}
+ },
+ .minSupportedVersion = TestHalVersion::AIDL_V3,
+ .referenced = {}
+ };
+ return model;
+}
+
+const auto dummy_test_model_mode_symmetric_int32_all_tensors_as_inputs = TestModelManager::get().add("mirror_pad_tensorflow_mode_symmetric_int32_all_tensors_as_inputs", get_test_model_mode_symmetric_int32_all_tensors_as_inputs());
+
+} // namespace generated_tests::mirror_pad_tensorflow
+
diff --git a/runtime/test/specs/AIDL_V3/mirror_pad.mod.py b/runtime/test/specs/AIDL_V3/mirror_pad.mod.py
new file mode 100644
index 0000000..661b6ca
--- /dev/null
+++ b/runtime/test/specs/AIDL_V3/mirror_pad.mod.py
@@ -0,0 +1,96 @@
+# Copyright (C) 2021 The Android Open Source Project
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import numpy
+import random
+
+def random_value(r):
+ # Compute a pseudorandom value in the range [0, 1) and scale it to
+ # make it more interesting for int32 variation and make it simple
+ # to specify quantized variation.
+ return 30 * r.random()
+
+# Generate test case for specified modes (0=reflect, 1=symmetric). If
+# clampReflectPadding is True, then while generating test for reflect,
+# accommodate padding that equals the maximum for symmetric and hence
+# exceeds by one the maximum for reflect, by clamping the padding to
+# the maximum for reflect.
+def test(name, seed, input_dims, orig_paddings, modes=[0, 1], clampReflectPadding=False):
+ for mode in modes:
+ r = random.Random()
+ r.seed(seed)
+
+ paddings = orig_paddings.copy()
+ if mode==0 and clampReflectPadding:
+ for i in range(0, len(input_dims)):
+ for leftright in [0, 1]:
+ padding_index = i * 2 + leftright
+ if paddings[padding_index] == input_dims[i]:
+ paddings[padding_index] = input_dims[i] - 1
+
+ input_tensor = Input("in", ("TENSOR_FLOAT32", input_dims))
+ padding_tensor = Parameter("padding", ("TENSOR_INT32", [len(input_dims), 2]), paddings)
+ output_dims = [sum(x) for x in zip(input_dims, paddings[0::2], paddings[1::2])]
+ output_tensor = Output("out", ("TENSOR_FLOAT32", output_dims))
+ model = Model().Operation("MIRROR_PAD", input_tensor, padding_tensor, mode).To(output_tensor)
+
+ input_data = [random_value(r) for x in range(0, numpy.prod(input_dims))]
+
+ numpy_input_data = numpy.reshape(input_data, input_dims)
+ numpy_paddings = list(zip(paddings[0::2], paddings[1::2]))
+ numpy_mode = "reflect" if mode==0 else "symmetric"
+ numpy_output_data = numpy.pad(numpy_input_data, numpy_paddings, mode=numpy_mode)
+
+ output_data = numpy_output_data.flatten().tolist()
+
+ quant8_asymm_type = ("TENSOR_QUANT8_ASYMM", 0.125, 4)
+ quant8_asymm = DataTypeConverter(name="quant8_asymm").Identify({
+ input_tensor: quant8_asymm_type,
+ output_tensor: quant8_asymm_type,
+ })
+ quant8_asymm_signed_type = ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, -9)
+ quant8_asymm_signed = DataTypeConverter(name="quant8_asymm_signed").Identify({
+ input_tensor: quant8_asymm_signed_type,
+ output_tensor: quant8_asymm_signed_type,
+ })
+
+ Example({
+ input_tensor: input_data,
+ output_tensor: output_data,
+ }, model=model, name=name + "_" + numpy_mode).AddVariations("float16", quant8_asymm, quant8_asymm_signed, "int32")
+
+
+# Test simple
+test("one", 0, [2, 3], [0, 1, 1, 2])
+
+# Test high rank
+test("two", 1, [1, 2, 1, 2, 1, 2, 1, 2, 1, 2], [0, 0, # dim=1
+ 0, 1, # dim=2
+ 0, 1, # dim=1
+ 1, 0, # dim=2
+ 1, 0, # dim=1
+ 1, 2, # dim=2
+ 1, 1, # dim=1
+ 2, 1, # dim=2
+ 0, 1, # dim=1
+ 0, 2], # dim=2
+ clampReflectPadding=True)
+
+# Test maxed-out padding values
+test("three", 2, [3, 4, 5, 6], [3, 3, # dim=3
+ 4, 2, # dim=4
+ 1, 5, # dim=5
+ 1, 1], # dim=6
+ modes=[1]) # symmetric
diff --git a/runtime/test/specs/AIDL_V3/mirror_pad_tensorflow.mod.py b/runtime/test/specs/AIDL_V3/mirror_pad_tensorflow.mod.py
new file mode 100644
index 0000000..667d6a6
--- /dev/null
+++ b/runtime/test/specs/AIDL_V3/mirror_pad_tensorflow.mod.py
@@ -0,0 +1,63 @@
+# Copyright (C) 2021 The Android Open Source Project
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# These examples are taken from the TensorFlow specification:
+#
+# https://www.tensorflow.org/api_docs/cc/class/tensorflow/ops/mirror-pad
+
+def test(name, input_dims, input_values, paddings, mode, output_dims, output_values):
+ t = Input("t", ("TENSOR_FLOAT32", input_dims))
+ paddings = Parameter("paddings", ("TENSOR_INT32", [len(input_dims), 2]), paddings)
+ output = Output("output", ("TENSOR_FLOAT32", output_dims))
+
+ model = Model().Operation("MIRROR_PAD", t, paddings, mode).To(output)
+
+ quant8_asymm_type = ("TENSOR_QUANT8_ASYMM", 0.5, 4)
+ quant8_asymm = DataTypeConverter(name="quant8_asymm").Identify({
+ t: quant8_asymm_type,
+ output: quant8_asymm_type,
+ })
+ quant8_asymm_signed_type = ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, -9)
+ quant8_asymm_signed = DataTypeConverter(name="quant8_asymm_signed").Identify({
+ t: quant8_asymm_signed_type,
+ output: quant8_asymm_signed_type,
+ })
+ Example({
+ t: input_values,
+ output: output_values,
+ }, model=model, name=name).AddVariations("float16", quant8_asymm, quant8_asymm_signed, "int32")
+
+test("summary",
+ [2, 3], [1, 2, 3, # input_dims, input_values
+ 4, 5, 6],
+ [1, 1, # paddings
+ 2, 2],
+ 1, # mode = SYMMETRIC
+ [4, 7], [2, 1, 1, 2, 3, 3, 2, # output_dims, output_values
+ 2, 1, 1, 2, 3, 3, 2,
+ 5, 4, 4, 5, 6, 6, 5,
+ 5, 4, 4, 5, 6, 6, 5])
+
+test("mode_reflect",
+ [3], [1, 2, 3], # input_dims, input_values
+ [0, 2], # paddings
+ 0, # mode = REFLECT
+ [5], [1, 2, 3, 2, 1]) # output_dims, output_values
+
+test("mode_symmetric",
+ [3], [1, 2, 3], # input_dims, input_values
+ [0, 2], # paddings
+ 1, # mode = SYMMETRIC
+ [5], [1, 2, 3, 3, 2]) # output_dims, output_values
diff --git a/tools/api/types.spec b/tools/api/types.spec
index 96e78e6..1922c77 100644
--- a/tools/api/types.spec
+++ b/tools/api/types.spec
@@ -6667,6 +6667,18 @@
/**
* Pads a tensor with mirrored values.
*
+ * This operator specifies one of two padding modes: REFLECT or SYMMETRIC.
+ * In the case of REFLECT mode, the mirroring excludes the border element
+ * on the padding side.
+ * In the case of SYMMETRIC mode, the mirroring includes the border element
+ * on the padding side.
+ *
+ * For example, if the input is the 1-D tensor `[1, 2, 3]` and the padding
+ * is `[0, 2]` (i.e., pad no elements before the first (and only) dimension,
+ * and two elements after the first (and only) dimension), then:
+ * - REFLECT mode produces the output `[1, 2, 3, 2, 1]`
+ * - SYMMETRIC mode produces the output `[1, 2, 3, 3, 2]`
+ *
* Supported tensor {@link %{OperandType}}:
* * {@link %{OperandTypeLinkPfx}TENSOR_FLOAT16}
* * {@link %{OperandTypeLinkPfx}TENSOR_FLOAT32}
@@ -6685,6 +6697,11 @@
* front of dimension i.
* padding[i, 1] specifies the number of elements to be padded after the
* end of dimension i.
+ * Each padding value must be nonnegative.
+ * In the case of REFLECT mode, each padding value must be less than the
+ * corresponding dimension.
+ * In the case of SYMMETRIC mode, each padding value must be less than or
+ * equal to the corresponding dimension.
* * 2: An {@link %{OperandTypeLinkPfx}INT32} scalar, specifying the mode.
* Options are 0:REFLECT and 1:SYMMETRIC.
*
