Add AHardwareBuffer support for NNAPI
- The main purpose for AHardwareBuffer support is for model inputs &
outputs.
- ANeuralNetworks_setOperandValueFromMemory only accepts BLOB mode
AHardwareBuffer.
- ANeuralNetworks_set[Input|Output]FromMemory can accepts non-BLOB mode
AHardwareBuffer. And for non-BLOB mode buffer, the entire buffer will
be used.
- There is no guarantee that arbitrary AHardwareBuffer can be used by
arbitrary devices. The execution must fail if the driver cannot
consume the buffer.
- No CPU fallback for AHardwareBuffer except BLOB mode.
Test: mm
Test: NeuralNetworksTest_static
Change-Id: I9d9ac95aea1e56b583c06e4f9c9afdaab1403152
Merged-In: I9d9ac95aea1e56b583c06e4f9c9afdaab1403152
(cherry picked from commit 5777040ee6f93f4060f7efb6cffaf5bff37f99d8)
diff --git a/runtime/ExecutionBuilder.cpp b/runtime/ExecutionBuilder.cpp
index c163f5b..8b04620 100644
--- a/runtime/ExecutionBuilder.cpp
+++ b/runtime/ExecutionBuilder.cpp
@@ -81,15 +81,14 @@
return ANEURALNETWORKS_NO_ERROR;
}
-int ModelArgumentInfo::setFromTemporaryMemory(const Operand& operand,
- uint32_t poolIndex, uint32_t offset) {
+int ModelArgumentInfo::setFromTemporaryMemory(const Operand& operand, uint32_t poolIndex,
+ uint32_t offset) {
int n = updateDimensionInfo(operand, nullptr);
if (n != ANEURALNETWORKS_NO_ERROR) {
return n;
}
state = ModelArgumentInfo::MEMORY;
- locationAndLength =
- {.poolIndex = poolIndex, .offset = offset, .length = sizeOfData(operand)};
+ locationAndLength = {.poolIndex = poolIndex, .offset = offset, .length = sizeOfData(operand)};
buffer = nullptr;
return ANEURALNETWORKS_NO_ERROR;
}
@@ -126,12 +125,12 @@
return ANEURALNETWORKS_NO_ERROR;
}
-ExecutionBuilder::ExecutionBuilder(const CompilationBuilder* compilation) :
- mModel(compilation->mModel),
- mPlan(&compilation->mPlan),
- mPartitioning(compilation->mPartitioning),
- mInputs(mModel->inputCount()),
- mOutputs(mModel->outputCount()) {
+ExecutionBuilder::ExecutionBuilder(const CompilationBuilder* compilation)
+ : mModel(compilation->mModel),
+ mPlan(&compilation->mPlan),
+ mPartitioning(compilation->mPartitioning),
+ mInputs(mModel->inputCount()),
+ mOutputs(mModel->outputCount()) {
VLOG(EXECUTION) << "ExecutionBuilder::ExecutionBuilder";
}
@@ -167,7 +166,12 @@
<< count;
return ANEURALNETWORKS_BAD_DATA;
}
- if (!memory->validateSize(offset, length)) {
+ // Both offset & length must be zero for Non-BLOB format AHardwareBuffer.
+ if (memory->getHidlMemory().name() == "hardware_buffer" && (offset != 0 || length != 0)) {
+ LOG(ERROR) << "ANeuralNetworksExecution_setInputFromMemory has non-zero offset and length"
+ << " for Non-BLOB format AHardwareBuffer.";
+ return ANEURALNETWORKS_BAD_DATA;
+ } else if (!memory->validateSize(offset, length)) {
return ANEURALNETWORKS_BAD_DATA;
}
// TODO validate the rest
@@ -176,8 +180,8 @@
length);
}
-int ExecutionBuilder::setOutput(uint32_t index, const ANeuralNetworksOperandType* type, void* buffer,
- size_t length) {
+int ExecutionBuilder::setOutput(uint32_t index, const ANeuralNetworksOperandType* type,
+ void* buffer, size_t length) {
uint32_t count = static_cast<uint32_t>(mOutputs.size());
if (index >= count) {
LOG(ERROR) << "ANeuralNetworksExecution_setOutput bad index " << index << " " << count;
@@ -207,7 +211,12 @@
<< count;
return ANEURALNETWORKS_BAD_DATA;
}
- if (!memory->validateSize(offset, length)) {
+ // Both offset & length must be zero for Non-BLOB format AHardwareBuffer.
+ if (memory->getHidlMemory().name() == "hardware_buffer" && (offset != 0 || length != 0)) {
+ LOG(ERROR) << "ANeuralNetworksExecution_setOutputFromMemory has non-zero offset and length"
+ << " for Non-BLOB format AHardwareBuffer.";
+ return ANEURALNETWORKS_BAD_DATA;
+ } else if (!memory->validateSize(offset, length)) {
return ANEURALNETWORKS_BAD_DATA;
}
// TODO validate the rest
@@ -281,8 +290,7 @@
// (2) If unsuccessful, attempt to execute the full model on CPU,
// ensure that executionCallback->notify() is called, and return
// false.
-static bool cpuFallbackPartial(const ExecutionBuilder* executionBuilder,
- const ExecutionPlan* plan,
+static bool cpuFallbackPartial(const ExecutionBuilder* executionBuilder, const ExecutionPlan* plan,
std::shared_ptr<ExecutionPlan::Controller> controller,
const sp<ExecutionCallback>& executionCallback) {
NNTRACE_RT(NNTRACE_PHASE_EXECUTION, "cpuFallbackPartial");
@@ -465,15 +473,16 @@
}
static void setRequestArgumentArray(const std::vector<ModelArgumentInfo>& argumentInfos,
- hidl_vec<RequestArgument>* ioInfos) {
+ hidl_vec<RequestArgument>* ioInfos) {
size_t count = argumentInfos.size();
ioInfos->resize(count);
for (size_t i = 0; i < count; i++) {
const auto& info = argumentInfos[i];
- (*ioInfos)[i] = { .hasNoValue = info.state == ModelArgumentInfo::HAS_NO_VALUE,
- .location = info.locationAndLength,
- .dimensions = info.dimensions,
- };
+ (*ioInfos)[i] = {
+ .hasNoValue = info.state == ModelArgumentInfo::HAS_NO_VALUE,
+ .location = info.locationAndLength,
+ .dimensions = info.dimensions,
+ };
}
}
@@ -506,12 +515,10 @@
case ModelArgumentInfo::UNSPECIFIED:
break;
case ModelArgumentInfo::MEMORY: {
- const uint32_t builderPoolIndex =
- builderInputOrOutput.locationAndLength.poolIndex;
+ const uint32_t builderPoolIndex = builderInputOrOutput.locationAndLength.poolIndex;
const Memory* memory = mExecutionBuilder->mMemories[builderPoolIndex];
const uint32_t executorPoolIndex = mMemories.add(memory);
- executorInputOrOutput->locationAndLength.poolIndex =
- executorPoolIndex;
+ executorInputOrOutput->locationAndLength.poolIndex = executorPoolIndex;
break;
}
}
@@ -528,7 +535,7 @@
return inputOrOutputInfo->setFromTemporaryMemory(inputOrOutputOperand, poolIndex, offset);
}
-static void logArguments(const char* kind, const std::vector<ModelArgumentInfo> &args) {
+static void logArguments(const char* kind, const std::vector<ModelArgumentInfo>& args) {
for (unsigned i = 0; i < args.size(); i++) {
const auto& arg = args[i];
std::string prefix = kind + std::string("[") + std::to_string(i) + "] = ";
@@ -538,10 +545,8 @@
break;
case ModelArgumentInfo::MEMORY:
VLOG(EXECUTION) << prefix << "MEMORY("
- << "pool=" << arg.locationAndLength.poolIndex
- << ", "
- << "off=" << arg.locationAndLength.offset
- << ")";
+ << "pool=" << arg.locationAndLength.poolIndex << ", "
+ << "off=" << arg.locationAndLength.offset << ")";
break;
case ModelArgumentInfo::HAS_NO_VALUE:
VLOG(EXECUTION) << prefix << "HAS_NO_VALUE";
@@ -590,7 +595,7 @@
// remove this entire block of code since it is a stale path that is only
// encountered on an #if-removed code.
ExecutionPreference preference =
- static_cast<ExecutionPreference>(ANEURALNETWORKS_PREFER_FAST_SINGLE_ANSWER);
+ static_cast<ExecutionPreference>(ANEURALNETWORKS_PREFER_FAST_SINGLE_ANSWER);
ErrorStatus prepareLaunchStatus =
mDevice->getInterface()->prepareModel(model, preference, preparedModelCallback);
if (prepareLaunchStatus != ErrorStatus::NONE) {
@@ -698,9 +703,8 @@
Return<ErrorStatus> callbackStatus = executionCallback->getStatus();
if (!callbackStatus.isOk() || callbackStatus != ErrorStatus::NONE) {
VLOG(EXECUTION) << "**Execution failed**";
- return callbackStatus.isOk()
- ? convertErrorStatusToResultCode(callbackStatus)
- : ANEURALNETWORKS_OP_FAILED;
+ return callbackStatus.isOk() ? convertErrorStatusToResultCode(callbackStatus)
+ : ANEURALNETWORKS_OP_FAILED;
}
// Copy the output data from shared memory to the output buffers.
@@ -770,7 +774,7 @@
for (ModelArgumentInfo& argumentInfo : argumentInfos) {
if (argumentInfo.state == ModelArgumentInfo::POINTER) {
argumentInfo.locationAndLength.poolIndex =
- static_cast<uint32_t>(requestPoolInfos.size());
+ static_cast<uint32_t>(requestPoolInfos.size());
argumentInfo.locationAndLength.offset = 0;
requestPoolInfos.emplace_back(static_cast<uint8_t*>(argumentInfo.buffer));
}
