| // Copyright 2022 Google LLC |
| // |
| // This source code is licensed under the BSD-style license found in the |
| // LICENSE file in the root directory of this source tree. |
| |
| #include <algorithm> |
| #include <array> |
| #include <cassert> |
| #include <cstddef> |
| #include <cstdint> |
| #include <limits> |
| #include <memory> |
| #include <numeric> |
| #include <random> |
| |
| #include <xnnpack.h> |
| #include <xnnpack/node-type.h> |
| #include <xnnpack/operator.h> |
| #include <xnnpack/subgraph.h> |
| |
| #include <gtest/gtest.h> |
| |
| template <typename T> class DepthToSpaceTest : public ::testing::Test { |
| protected: |
| DepthToSpaceTest() |
| { |
| random_device = std::unique_ptr<std::random_device>(new std::random_device()); |
| rng = std::mt19937((*random_device)()); |
| dim_dist = std::uniform_int_distribution<size_t>(1, 9); |
| i8dist = |
| std::uniform_int_distribution<int32_t>(std::numeric_limits<int8_t>::min(), std::numeric_limits<int8_t>::max()); |
| u8dist = |
| std::uniform_int_distribution<int32_t>(std::numeric_limits<uint8_t>::min(), std::numeric_limits<uint8_t>::max()); |
| scale_dist = std::uniform_real_distribution<float>(0.1f, 10.0f); |
| f32dist = std::uniform_real_distribution<float>(0.01f, 1.0f); |
| |
| input_dims = RandomShape(4); |
| block_size = std::uniform_int_distribution<uint32_t>(2, 10)(rng); |
| uint32_t output_channels = dim_dist(rng); |
| output_dims = {input_dims[0], input_dims[1] * block_size, input_dims[2] * block_size, output_channels}; |
| input_dims[3] = block_size * block_size * output_channels; |
| |
| size_t num_output_elements = NumElements(output_dims); |
| input = std::vector<T>(NumElements(input_dims) + XNN_EXTRA_BYTES / sizeof(T)); |
| operator_output = std::vector<T>(num_output_elements); |
| subgraph_output = std::vector<T>(num_output_elements); |
| } |
| |
| size_t NumElements(std::vector<size_t>& dims) |
| { |
| return std::accumulate(dims.begin(), dims.end(), size_t(1), std::multiplies<size_t>()); |
| } |
| |
| std::vector<size_t> RandomShape(size_t num_dims) |
| { |
| std::vector<size_t> dims(num_dims); |
| std::generate(dims.begin(), dims.end(), [&] { return dim_dist(rng); }); |
| return dims; |
| } |
| |
| size_t batch_size() |
| { |
| assert(input_dims[0] == output_dims[0]); |
| return input_dims[0]; |
| } |
| |
| size_t input_height() { return input_dims[1]; } |
| size_t input_width() { return input_dims[2]; } |
| size_t input_channel() { return input_dims[3]; } |
| size_t output_channel() { return output_dims[3]; } |
| |
| std::unique_ptr<std::random_device> random_device; |
| std::mt19937 rng; |
| std::uniform_int_distribution<size_t> dim_dist; |
| std::uniform_real_distribution<float> scale_dist; |
| std::uniform_int_distribution<int32_t> i8dist; |
| std::uniform_int_distribution<int32_t> u8dist; |
| std::uniform_real_distribution<float> f32dist; |
| |
| std::vector<size_t> input_dims; |
| std::vector<size_t> output_dims; |
| |
| std::vector<T> input; |
| std::vector<T> operator_output; |
| std::vector<T> subgraph_output; |
| |
| uint32_t block_size; |
| |
| uint32_t input_id; |
| uint32_t output_id; |
| }; |
| |
| using DepthToSpaceTestQS8 = DepthToSpaceTest<int8_t>; |
| using DepthToSpaceTestQU8 = DepthToSpaceTest<uint8_t>; |
| using DepthToSpaceTestF32 = DepthToSpaceTest<float>; |
| |
| TEST_F(DepthToSpaceTestQS8, define) |
| { |
| const int32_t input_zero_point = i8dist(rng); |
| const float input_scale = scale_dist(rng); |
| const int32_t output_zero_point = input_zero_point; |
| const float output_scale = input_scale; |
| |
| ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr)); |
| |
| xnn_subgraph_t subgraph = nullptr; |
| ASSERT_EQ(xnn_status_success, xnn_create_subgraph(/*external_value_ids=*/2, /*flags=*/0, &subgraph)); |
| std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph); |
| |
| input_id = XNN_INVALID_NODE_ID; |
| ASSERT_EQ( |
| xnn_status_success, xnn_define_quantized_tensor_value( |
| subgraph, xnn_datatype_qint8, input_zero_point, input_scale, input_dims.size(), |
| input_dims.data(), nullptr, 0, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id)); |
| ASSERT_NE(input_id, XNN_INVALID_NODE_ID); |
| |
| output_id = XNN_INVALID_NODE_ID; |
| ASSERT_EQ( |
| xnn_status_success, xnn_define_quantized_tensor_value( |
| subgraph, xnn_datatype_qint8, output_zero_point, output_scale, output_dims.size(), |
| output_dims.data(), nullptr, 1, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id)); |
| ASSERT_NE(output_id, XNN_INVALID_NODE_ID); |
| |
| ASSERT_EQ(xnn_status_success, xnn_define_depth_to_space(subgraph, input_id, output_id, block_size, /*flags=*/0)); |
| |
| ASSERT_EQ(subgraph->num_nodes, 1); |
| const struct xnn_node* node = &subgraph->nodes[0]; |
| ASSERT_EQ(node->type, xnn_node_type_depth_to_space); |
| ASSERT_EQ(node->compute_type, xnn_compute_type_qs8); |
| ASSERT_EQ(node->num_inputs, 1); |
| ASSERT_EQ(node->inputs[0], input_id); |
| ASSERT_EQ(node->num_outputs, 1); |
| ASSERT_EQ(node->outputs[0], output_id); |
| ASSERT_EQ(node->flags, 0); |
| } |
| |
| TEST_F(DepthToSpaceTestQU8, define) |
| { |
| const int32_t input_zero_point = u8dist(rng); |
| const float input_scale = scale_dist(rng); |
| const int32_t output_zero_point = input_zero_point; |
| const float output_scale = input_scale; |
| uint32_t block_size = std::uniform_int_distribution<uint32_t>(2, 10)(rng); |
| |
| ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr)); |
| |
| xnn_subgraph_t subgraph = nullptr; |
| ASSERT_EQ(xnn_status_success, xnn_create_subgraph(/*external_value_ids=*/2, /*flags=*/0, &subgraph)); |
| std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph); |
| |
| input_id = XNN_INVALID_NODE_ID; |
| ASSERT_EQ( |
| xnn_status_success, xnn_define_quantized_tensor_value( |
| subgraph, xnn_datatype_quint8, input_zero_point, input_scale, input_dims.size(), |
| input_dims.data(), nullptr, 0, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id)); |
| ASSERT_NE(input_id, XNN_INVALID_NODE_ID); |
| |
| output_id = XNN_INVALID_NODE_ID; |
| ASSERT_EQ( |
| xnn_status_success, xnn_define_quantized_tensor_value( |
| subgraph, xnn_datatype_quint8, output_zero_point, output_scale, output_dims.size(), |
| output_dims.data(), nullptr, 1, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id)); |
| ASSERT_NE(output_id, XNN_INVALID_NODE_ID); |
| |
| ASSERT_EQ(xnn_status_success, xnn_define_depth_to_space(subgraph, input_id, output_id, block_size, /*flags=*/0)); |
| |
| ASSERT_EQ(subgraph->num_nodes, 1); |
| const struct xnn_node* node = &subgraph->nodes[0]; |
| ASSERT_EQ(node->type, xnn_node_type_depth_to_space); |
| ASSERT_EQ(node->compute_type, xnn_compute_type_qu8); |
| ASSERT_EQ(node->num_inputs, 1); |
| ASSERT_EQ(node->inputs[0], input_id); |
| ASSERT_EQ(node->num_outputs, 1); |
| ASSERT_EQ(node->outputs[0], output_id); |
| ASSERT_EQ(node->flags, 0); |
| } |
| |
| TEST_F(DepthToSpaceTestF32, define) |
| { |
| uint32_t block_size = std::uniform_int_distribution<uint32_t>(2, 10)(rng); |
| |
| ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr)); |
| |
| xnn_subgraph_t subgraph = nullptr; |
| ASSERT_EQ(xnn_status_success, xnn_create_subgraph(/*external_value_ids=*/2, /*flags=*/0, &subgraph)); |
| std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph); |
| |
| input_id = XNN_INVALID_NODE_ID; |
| ASSERT_EQ( |
| xnn_status_success, xnn_define_tensor_value( |
| subgraph, xnn_datatype_fp32, input_dims.size(), input_dims.data(), nullptr, 0, |
| /*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id)); |
| ASSERT_NE(input_id, XNN_INVALID_NODE_ID); |
| |
| output_id = XNN_INVALID_NODE_ID; |
| ASSERT_EQ( |
| xnn_status_success, xnn_define_tensor_value( |
| subgraph, xnn_datatype_fp32, output_dims.size(), output_dims.data(), nullptr, 1, |
| /*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id)); |
| ASSERT_NE(output_id, XNN_INVALID_NODE_ID); |
| |
| ASSERT_EQ(xnn_status_success, xnn_define_depth_to_space(subgraph, input_id, output_id, block_size, /*flags=*/0)); |
| |
| ASSERT_EQ(subgraph->num_nodes, 1); |
| const struct xnn_node* node = &subgraph->nodes[0]; |
| ASSERT_EQ(node->type, xnn_node_type_depth_to_space); |
| ASSERT_EQ(node->compute_type, xnn_compute_type_fp32); |
| ASSERT_EQ(node->num_inputs, 1); |
| ASSERT_EQ(node->inputs[0], input_id); |
| ASSERT_EQ(node->num_outputs, 1); |
| ASSERT_EQ(node->outputs[0], output_id); |
| ASSERT_EQ(node->flags, 0); |
| } |
| |
| TEST_F(DepthToSpaceTestQS8, matches_operator_api) |
| { |
| const int32_t input_zero_point = i8dist(rng); |
| const float input_scale = scale_dist(rng); |
| const int32_t output_zero_point = input_zero_point; |
| const float output_scale = input_scale; |
| std::generate(input.begin(), input.end(), [&]() { return i8dist(rng); }); |
| std::fill(operator_output.begin(), operator_output.end(), INT8_C(0xA5)); |
| std::fill(subgraph_output.begin(), subgraph_output.end(), INT8_C(0xA5)); |
| |
| ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr)); |
| |
| // Call operator API. |
| xnn_operator_t op = nullptr; |
| const xnn_status status = xnn_create_depth_to_space_nhwc_x8( |
| output_channel(), input_channel(), output_channel(), block_size, /*flags=*/0, &op); |
| if (status == xnn_status_unsupported_hardware) { |
| GTEST_SKIP(); |
| } |
| ASSERT_EQ(xnn_status_success, status); |
| ASSERT_NE(nullptr, op); |
| std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator); |
| |
| ASSERT_EQ( |
| xnn_status_success, |
| xnn_setup_depth_to_space_nhwc_x8( |
| op, batch_size(), input_height(), input_width(), input.data(), operator_output.data(), /*threadpool=*/nullptr)); |
| ASSERT_EQ(xnn_status_success, xnn_run_operator(op, /*threadpool=*/nullptr)); |
| |
| // Call subgraph API. |
| xnn_subgraph_t subgraph = nullptr; |
| ASSERT_EQ(xnn_status_success, xnn_create_subgraph(/*external_value_ids=*/2, /*flags=*/0, &subgraph)); |
| std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph); |
| input_id = XNN_INVALID_NODE_ID; |
| ASSERT_EQ( |
| xnn_status_success, |
| xnn_define_quantized_tensor_value( |
| subgraph, xnn_datatype_qint8, input_zero_point, input_scale, input_dims.size(), input_dims.data(), nullptr, |
| /*external_id=*/0, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id)); |
| ASSERT_NE(input_id, XNN_INVALID_NODE_ID); |
| |
| output_id = XNN_INVALID_NODE_ID; |
| ASSERT_EQ( |
| xnn_status_success, |
| xnn_define_quantized_tensor_value( |
| subgraph, xnn_datatype_qint8, output_zero_point, output_scale, output_dims.size(), output_dims.data(), nullptr, |
| /*external_id=*/1, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id)); |
| ASSERT_NE(output_id, XNN_INVALID_NODE_ID); |
| |
| ASSERT_EQ(xnn_status_success, xnn_define_depth_to_space(subgraph, input_id, output_id, block_size, /*flags=*/0)); |
| |
| xnn_runtime_t runtime = nullptr; |
| ASSERT_EQ(xnn_status_success, xnn_create_runtime_v3(subgraph, nullptr, nullptr, /*flags=*/0, &runtime)); |
| ASSERT_NE(nullptr, runtime); |
| std::unique_ptr<xnn_runtime, decltype(&xnn_delete_runtime)> auto_runtime(runtime, xnn_delete_runtime); |
| |
| std::array<xnn_external_value, 2> external = { |
| xnn_external_value{input_id, input.data()}, xnn_external_value{output_id, subgraph_output.data()}}; |
| ASSERT_EQ(xnn_status_success, xnn_setup_runtime(runtime, external.size(), external.data())); |
| ASSERT_EQ(xnn_status_success, xnn_invoke_runtime(runtime)); |
| |
| ASSERT_EQ(subgraph_output, operator_output); |
| } |
| |
| TEST_F(DepthToSpaceTestQU8, matches_operator_api) |
| { |
| const int32_t input_zero_point = u8dist(rng); |
| const float input_scale = scale_dist(rng); |
| const int32_t output_zero_point = input_zero_point; |
| const float output_scale = input_scale; |
| std::generate(input.begin(), input.end(), [&]() { return u8dist(rng); }); |
| std::fill(operator_output.begin(), operator_output.end(), UINT8_C(0xA5)); |
| std::fill(subgraph_output.begin(), subgraph_output.end(), UINT8_C(0xA5)); |
| |
| ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr)); |
| |
| // Call operator API. |
| xnn_operator_t op = nullptr; |
| const xnn_status status = xnn_create_depth_to_space_nhwc_x8( |
| output_channel(), input_channel(), output_channel(), block_size, /*flags=*/0, &op); |
| if (status == xnn_status_unsupported_hardware) { |
| GTEST_SKIP(); |
| } |
| ASSERT_EQ(xnn_status_success, status); |
| ASSERT_NE(nullptr, op); |
| std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator); |
| |
| ASSERT_EQ( |
| xnn_status_success, |
| xnn_setup_depth_to_space_nhwc_x8( |
| op, batch_size(), input_height(), input_width(), input.data(), operator_output.data(), /*threadpool=*/nullptr)); |
| ASSERT_EQ(xnn_status_success, xnn_run_operator(op, /*threadpool=*/nullptr)); |
| |
| // Call subgraph API. |
| xnn_subgraph_t subgraph = nullptr; |
| ASSERT_EQ(xnn_status_success, xnn_create_subgraph(/*external_value_ids=*/2, /*flags=*/0, &subgraph)); |
| std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph); |
| input_id = XNN_INVALID_NODE_ID; |
| ASSERT_EQ( |
| xnn_status_success, |
| xnn_define_quantized_tensor_value( |
| subgraph, xnn_datatype_quint8, input_zero_point, input_scale, input_dims.size(), input_dims.data(), nullptr, |
| /*external_id=*/0, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id)); |
| ASSERT_NE(input_id, XNN_INVALID_NODE_ID); |
| |
| output_id = XNN_INVALID_NODE_ID; |
| ASSERT_EQ( |
| xnn_status_success, |
| xnn_define_quantized_tensor_value( |
| subgraph, xnn_datatype_quint8, output_zero_point, output_scale, output_dims.size(), output_dims.data(), nullptr, |
| /*external_id=*/1, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id)); |
| ASSERT_NE(output_id, XNN_INVALID_NODE_ID); |
| |
| ASSERT_EQ(xnn_status_success, xnn_define_depth_to_space(subgraph, input_id, output_id, block_size, /*flags=*/0)); |
| |
| xnn_runtime_t runtime = nullptr; |
| ASSERT_EQ(xnn_status_success, xnn_create_runtime_v3(subgraph, nullptr, nullptr, /*flags=*/0, &runtime)); |
| ASSERT_NE(nullptr, runtime); |
| std::unique_ptr<xnn_runtime, decltype(&xnn_delete_runtime)> auto_runtime(runtime, xnn_delete_runtime); |
| |
| std::array<xnn_external_value, 2> external = { |
| xnn_external_value{input_id, input.data()}, xnn_external_value{output_id, subgraph_output.data()}}; |
| ASSERT_EQ(xnn_status_success, xnn_setup_runtime(runtime, external.size(), external.data())); |
| ASSERT_EQ(xnn_status_success, xnn_invoke_runtime(runtime)); |
| |
| ASSERT_EQ(subgraph_output, operator_output); |
| } |
| |
| TEST_F(DepthToSpaceTestF32, matches_operator_api) |
| { |
| std::uniform_real_distribution<float> f32dist(-255.0f, 255.0f); |
| std::generate(input.begin(), input.end(), [&]() { return f32dist(rng); }); |
| std::fill(operator_output.begin(), operator_output.end(), nanf("")); |
| std::fill(subgraph_output.begin(), subgraph_output.end(), nanf("")); |
| |
| ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr)); |
| |
| // Call operator API. |
| xnn_operator_t op = nullptr; |
| const xnn_status status = xnn_create_depth_to_space_nhwc_x32( |
| output_channel(), input_channel(), output_channel(), block_size, /*flags=*/0, &op); |
| if (status == xnn_status_unsupported_hardware) { |
| GTEST_SKIP(); |
| } |
| |
| ASSERT_EQ(xnn_status_success, status); |
| ASSERT_NE(nullptr, op); |
| std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator); |
| |
| ASSERT_EQ( |
| xnn_status_success, |
| xnn_setup_depth_to_space_nhwc_x32( |
| op, batch_size(), input_height(), input_width(), input.data(), operator_output.data(), /*threadpool=*/nullptr)); |
| |
| ASSERT_EQ(xnn_status_success, xnn_run_operator(op, /*threadpool=*/nullptr)); |
| |
| // Call subgraph API. |
| xnn_subgraph_t subgraph = nullptr; |
| ASSERT_EQ(xnn_status_success, xnn_create_subgraph(/*external_value_ids=*/2, /*flags=*/0, &subgraph)); |
| std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph); |
| input_id = XNN_INVALID_NODE_ID; |
| ASSERT_EQ( |
| xnn_status_success, xnn_define_tensor_value( |
| subgraph, xnn_datatype_fp32, input_dims.size(), input_dims.data(), nullptr, /*external_id=*/0, |
| /*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id)); |
| ASSERT_NE(input_id, XNN_INVALID_NODE_ID); |
| |
| output_id = XNN_INVALID_NODE_ID; |
| ASSERT_EQ( |
| xnn_status_success, |
| xnn_define_tensor_value( |
| subgraph, xnn_datatype_fp32, output_dims.size(), output_dims.data(), nullptr, /*external_id=*/1, |
| /*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id)); |
| ASSERT_NE(output_id, XNN_INVALID_NODE_ID); |
| |
| xnn_runtime_t runtime = nullptr; |
| ASSERT_EQ(xnn_status_success, xnn_define_depth_to_space(subgraph, input_id, output_id, block_size, /*flags=*/0)); |
| ASSERT_EQ(xnn_status_success, xnn_create_runtime_v3(subgraph, nullptr, nullptr, /*flags=*/0, &runtime)); |
| ASSERT_NE(nullptr, runtime); |
| std::unique_ptr<xnn_runtime, decltype(&xnn_delete_runtime)> auto_runtime(runtime, xnn_delete_runtime); |
| std::array<xnn_external_value, 2> external = { |
| xnn_external_value{input_id, input.data()}, xnn_external_value{output_id, subgraph_output.data()}}; |
| ASSERT_EQ(xnn_status_success, xnn_setup_runtime(runtime, external.size(), external.data())); |
| ASSERT_EQ(xnn_status_success, xnn_invoke_runtime(runtime)); |
| |
| ASSERT_EQ(subgraph_output, operator_output); |
| } |