diff options
Diffstat (limited to 'delegate/src/test')
-rw-r--r-- | delegate/src/test/PackTest.cpp | 516 | ||||
-rw-r--r-- | delegate/src/test/PackTestHelper.hpp | 185 |
2 files changed, 701 insertions, 0 deletions
diff --git a/delegate/src/test/PackTest.cpp b/delegate/src/test/PackTest.cpp new file mode 100644 index 0000000000..aea903bcd0 --- /dev/null +++ b/delegate/src/test/PackTest.cpp @@ -0,0 +1,516 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "PackTestHelper.hpp" + +#include <armnn_delegate.hpp> + +#include <flatbuffers/flatbuffers.h> +#include <tensorflow/lite/schema/schema_generated.h> + +#include <doctest/doctest.h> + +namespace armnnDelegate +{ + +template <typename T> +void PackFp32Axis0Test(tflite::TensorType tensorType, std::vector<armnn::BackendId>& backends) +{ + std::vector<int32_t> inputShape { 3, 2, 3 }; + std::vector<int32_t> expectedOutputShape { 2, 3, 2, 3 }; + + std::vector<std::vector<T>> inputValues; + inputValues.push_back( + { + 1, 2, 3, + 4, 5, 6, + + 7, 8, 9, + 10, 11, 12, + + 13, 14, 15, + 16, 17, 18 + }); + + inputValues.push_back( + { + 19, 20, 21, + 22, 23, 24, + + 25, 26, 27, + 28, 29, 30, + + 31, 32, 33, + 34, 35, 36 + }); + + std::vector<T> expectedOutputValues = + { + 1, 2, 3, + 4, 5, 6, + + 7, 8, 9, + 10, 11, 12, + + 13, 14, 15, + 16, 17, 18, + + + 19, 20, 21, + 22, 23, 24, + + 25, 26, 27, + 28, 29, 30, + + 31, 32, 33, + 34, 35, 36 + }; + + PackTest<T>(tflite::BuiltinOperator_PACK, + tensorType, + backends, + inputShape, + expectedOutputShape, + inputValues, + expectedOutputValues, + 0); +} + +template <typename T> +void PackFp32Axis1Test(tflite::TensorType tensorType, std::vector<armnn::BackendId>& backends) +{ + std::vector<int32_t> inputShape { 3, 2, 3 }; + std::vector<int32_t> expectedOutputShape { 3, 2, 2, 3 }; + + std::vector<std::vector<T>> inputValues; + inputValues.push_back( + { + 1, 2, 3, + 4, 5, 6, + + 7, 8, 9, + 10, 11, 12, + + 13, 14, 15, + 16, 17, 18 + }); + + inputValues.push_back( + { + 19, 20, 21, + 22, 23, 24, + + 25, 26, 27, + 28, 29, 30, + + 31, 32, 33, + 34, 35, 36 + }); + + std::vector<T> expectedOutputValues = + { + 1, 2, 3, + 4, 5, 6, + + 19, 20, 21, + 22, 23, 24, + + + 7, 8, 9, + 10, 11, 12, + + 25, 26, 27, + 28, 29, 30, + + + 13, 14, 15, + 16, 17, 18, + + 31, 32, 33, + 34, 35, 36 + }; + + PackTest<T>(tflite::BuiltinOperator_PACK, + tensorType, + backends, + inputShape, + expectedOutputShape, + inputValues, + expectedOutputValues, + 1); +} + +template <typename T> +void PackFp32Axis2Test(tflite::TensorType tensorType, std::vector<armnn::BackendId>& backends) +{ + std::vector<int32_t> inputShape { 3, 2, 3 }; + std::vector<int32_t> expectedOutputShape { 3, 2, 2, 3 }; + + std::vector<std::vector<T>> inputValues; + inputValues.push_back( + { + 1, 2, 3, + 4, 5, 6, + + 7, 8, 9, + 10, 11, 12, + + 13, 14, 15, + 16, 17, 18 + }); + + inputValues.push_back( + { + 19, 20, 21, + 22, 23, 24, + + 25, 26, 27, + 28, 29, 30, + + 31, 32, 33, + 34, 35, 36 + }); + + std::vector<float> expectedOutputValues = + { + 1, 2, 3, + 19, 20, 21, + + 4, 5, 6, + 22, 23, 24, + + 7, 8, 9, + 25, 26, 27, + + 10, 11, 12, + 28, 29, 30, + + 13, 14, 15, + 31, 32, 33, + + 16, 17, 18, + 34, 35, 36 + }; + + PackTest<T>(tflite::BuiltinOperator_PACK, + tensorType, + backends, + inputShape, + expectedOutputShape, + inputValues, + expectedOutputValues, + 2); +} + +template <typename T> +void PackFp32Axis3Test(tflite::TensorType tensorType, std::vector<armnn::BackendId>& backends) +{ + std::vector<int32_t> inputShape { 3, 2, 3 }; + std::vector<int32_t> expectedOutputShape { 3, 2, 3, 2 }; + + std::vector<std::vector<T>> inputValues; + inputValues.push_back( + { + 1, 2, 3, + 4, 5, 6, + + 7, 8, 9, + 10, 11, 12, + + 13, 14, 15, + 16, 17, 18 + }); + + inputValues.push_back( + { + 19, 20, 21, + 22, 23, 24, + + 25, 26, 27, + 28, 29, 30, + + 31, 32, 33, + 34, 35, 36 + }); + + std::vector<T> expectedOutputValues = + { + 1, 19, + 2, 20, + 3, 21, + + 4, 22, + 5, 23, + 6, 24, + + + 7, 25, + 8, 26, + 9, 27, + + 10, 28, + 11, 29, + 12, 30, + + + 13, 31, + 14, 32, + 15, 33, + + 16, 34, + 17, 35, + 18, 36 + }; + + PackTest<T>(tflite::BuiltinOperator_PACK, + tflite::TensorType_FLOAT32, + backends, + inputShape, + expectedOutputShape, + inputValues, + expectedOutputValues, + 3); +} + +template <typename T> +void PackFp32Inputs3Test(tflite::TensorType tensorType, std::vector<armnn::BackendId>& backends) +{ + std::vector<int32_t> inputShape { 3, 3 }; + std::vector<int32_t> expectedOutputShape { 3, 3, 3 }; + + std::vector<std::vector<T>> inputValues; + inputValues.push_back( + { + 1, 2, 3, + 4, 5, 6, + 7, 8, 9 + }); + + inputValues.push_back( + { + 10, 11, 12, + 13, 14, 15, + 16, 17, 18 + }); + + inputValues.push_back( + { + 19, 20, 21, + 22, 23, 24, + 25, 26, 27 + }); + + std::vector<T> expectedOutputValues = + { + 1, 2, 3, + 10, 11, 12, + 19, 20, 21, + + 4, 5, 6, + 13, 14, 15, + 22, 23, 24, + + 7, 8, 9, + 16, 17, 18, + 25, 26, 27 + }; + + PackTest<T>(tflite::BuiltinOperator_PACK, + tensorType, + backends, + inputShape, + expectedOutputShape, + inputValues, + expectedOutputValues, + 1); +} + +TEST_SUITE("Pack_CpuAccTests") +{ + +// Fp32 +TEST_CASE ("Pack_Fp32_Axis0_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuAcc}; + PackFp32Axis0Test<float>(tflite::TensorType_FLOAT32, backends); +} + +TEST_CASE ("Pack_Fp32_Axis1_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuAcc}; + PackFp32Axis1Test<float>(tflite::TensorType_FLOAT32, backends); +} + +TEST_CASE ("Pack_Fp32_Axis2_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuAcc}; + PackFp32Axis2Test<float>(tflite::TensorType_FLOAT32, backends); +} + +TEST_CASE ("Pack_Fp32_Axis3_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuAcc}; + PackFp32Axis3Test<float>(tflite::TensorType_FLOAT32, backends); +} + +TEST_CASE ("Pack_Fp32_Inputs3_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuAcc}; + PackFp32Inputs3Test<float>(tflite::TensorType_FLOAT32, backends); +} + +// Uint8 +TEST_CASE ("Pack_Uint8_Axis0_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuAcc}; + PackFp32Axis0Test<uint8_t>(tflite::TensorType_UINT8, backends); +} + +TEST_CASE ("Pack_Uint8_Inputs3_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuAcc}; + PackFp32Inputs3Test<uint8_t>(tflite::TensorType_UINT8, backends); +} + +// Uint8 +TEST_CASE ("Pack_Int8_Axis0_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuAcc}; + PackFp32Axis0Test<int8_t>(tflite::TensorType_INT8, backends); +} + +TEST_CASE ("Pack_Int8_Inputs3_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuAcc}; + PackFp32Inputs3Test<int8_t>(tflite::TensorType_INT8, backends); +} + +} + +TEST_SUITE("Pack_GpuAccTests") +{ + +// Fp32 +TEST_CASE ("Pack_Fp32_Axis0_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc}; + PackFp32Axis0Test<float>(tflite::TensorType_FLOAT32, backends); +} + +TEST_CASE ("Pack_Fp32_Axis1_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc}; + PackFp32Axis1Test<float>(tflite::TensorType_FLOAT32, backends); +} + +TEST_CASE ("Pack_Fp32_Axis2_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc}; + PackFp32Axis2Test<float>(tflite::TensorType_FLOAT32, backends); +} + +TEST_CASE ("Pack_Fp32_Axis3_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc}; + PackFp32Axis3Test<float>(tflite::TensorType_FLOAT32, backends); +} + +TEST_CASE ("Pack_Fp32_Inputs3_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc}; + PackFp32Inputs3Test<float>(tflite::TensorType_FLOAT32, backends); +} + +// Uint8 +TEST_CASE ("Pack_Uint8_Axis0_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc}; + PackFp32Axis0Test<uint8_t>(tflite::TensorType_UINT8, backends); +} + +TEST_CASE ("Pack_Uint8_Inputs3_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc}; + PackFp32Inputs3Test<uint8_t>(tflite::TensorType_UINT8, backends); +} + +// Int8 +TEST_CASE ("Pack_Int8_Axis0_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc}; + PackFp32Axis0Test<int8_t>(tflite::TensorType_INT8, backends); +} + +TEST_CASE ("Pack_Int8_Inputs3_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc}; + PackFp32Inputs3Test<int8_t>(tflite::TensorType_INT8, backends); +} + +} + +TEST_SUITE("Pack_CpuRefTests") +{ + +// Fp32 +TEST_CASE ("Pack_Fp32_Axis0_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef}; + PackFp32Axis0Test<float>(tflite::TensorType_FLOAT32, backends); +} + +TEST_CASE ("Pack_Fp32_Axis1_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef}; + PackFp32Axis1Test<float>(tflite::TensorType_FLOAT32, backends); +} + +TEST_CASE ("Pack_Fp32_Axis2_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef}; + PackFp32Axis2Test<float>(tflite::TensorType_FLOAT32, backends); +} + +TEST_CASE ("Pack_Fp32_Axis3_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef}; + PackFp32Axis3Test<float>(tflite::TensorType_FLOAT32, backends); +} + +TEST_CASE ("Pack_Fp32_Inputs3_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef}; + PackFp32Inputs3Test<float>(tflite::TensorType_FLOAT32, backends); +} + +// Uint8 +TEST_CASE ("Pack_Uint8_Axis0_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef}; + PackFp32Axis0Test<uint8_t>(tflite::TensorType_UINT8, backends); +} + +TEST_CASE ("Pack_Uint8_Inputs3_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef}; + PackFp32Inputs3Test<uint8_t>(tflite::TensorType_UINT8, backends); +} + +// Int8 +TEST_CASE ("Pack_Int8_Axis0_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef}; + PackFp32Axis0Test<int8_t>(tflite::TensorType_INT8, backends); +} + +TEST_CASE ("Pack_Int8_Inputs3_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef}; + PackFp32Inputs3Test<int8_t>(tflite::TensorType_INT8, backends); +} + +} + +} // namespace armnnDelegate
\ No newline at end of file diff --git a/delegate/src/test/PackTestHelper.hpp b/delegate/src/test/PackTestHelper.hpp new file mode 100644 index 0000000000..0869228326 --- /dev/null +++ b/delegate/src/test/PackTestHelper.hpp @@ -0,0 +1,185 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "TestUtils.hpp" + +#include <armnn_delegate.hpp> + +#include <flatbuffers/flatbuffers.h> +#include <tensorflow/lite/interpreter.h> +#include <tensorflow/lite/kernels/register.h> +#include <tensorflow/lite/model.h> +#include <tensorflow/lite/schema/schema_generated.h> +#include <tensorflow/lite/version.h> + +#include <doctest/doctest.h> + +#include <string> + +namespace +{ + +std::vector<char> CreatePackTfLiteModel(tflite::BuiltinOperator packOperatorCode, + tflite::TensorType tensorType, + std::vector<int32_t>& inputTensorShape, + const std::vector <int32_t>& outputTensorShape, + const int32_t inputTensorNum, + unsigned int axis = 0, + float quantScale = 1.0f, + int quantOffset = 0) +{ + using namespace tflite; + flatbuffers::FlatBufferBuilder flatBufferBuilder; + + std::vector<flatbuffers::Offset<tflite::Buffer>> buffers; + buffers.push_back(CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({}))); + + auto quantizationParameters = + CreateQuantizationParameters(flatBufferBuilder, + 0, + 0, + flatBufferBuilder.CreateVector<float>({ quantScale }), + flatBufferBuilder.CreateVector<int64_t>({ quantOffset })); + + std::vector<int32_t> operatorInputs{}; + const std::vector<int32_t> operatorOutputs{inputTensorNum}; + std::vector<int> subgraphInputs{}; + const std::vector<int> subgraphOutputs{inputTensorNum}; + + std::vector<flatbuffers::Offset<Tensor>> tensors(inputTensorNum + 1); + for (int i = 0; i < inputTensorNum; ++i) + { + tensors[i] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(), + inputTensorShape.size()), + tensorType, + 0, + flatBufferBuilder.CreateString("input" + std::to_string(i)), + quantizationParameters); + + // Add number of inputs to vector. + operatorInputs.push_back(i); + subgraphInputs.push_back(i); + } + + // Create output tensor + tensors[inputTensorNum] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), + outputTensorShape.size()), + tensorType, + 0, + flatBufferBuilder.CreateString("output"), + quantizationParameters); + + // create operator + tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_PackOptions; + flatbuffers::Offset<void> operatorBuiltinOptions = + CreatePackOptions(flatBufferBuilder, inputTensorNum, axis).Union(); + + flatbuffers::Offset <Operator> packOperator = + CreateOperator(flatBufferBuilder, + 0, + flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), + flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), + operatorBuiltinOptionsType, + operatorBuiltinOptions); + + flatbuffers::Offset <SubGraph> subgraph = + CreateSubGraph(flatBufferBuilder, + flatBufferBuilder.CreateVector(tensors.data(), tensors.size()), + flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()), + flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()), + flatBufferBuilder.CreateVector(&packOperator, 1)); + + flatbuffers::Offset <flatbuffers::String> modelDescription = + flatBufferBuilder.CreateString("ArmnnDelegate: Pack Operator Model"); + flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, packOperatorCode); + + flatbuffers::Offset <Model> flatbufferModel = + CreateModel(flatBufferBuilder, + TFLITE_SCHEMA_VERSION, + flatBufferBuilder.CreateVector(&operatorCode, 1), + flatBufferBuilder.CreateVector(&subgraph, 1), + modelDescription, + flatBufferBuilder.CreateVector(buffers.data(), buffers.size())); + + flatBufferBuilder.Finish(flatbufferModel); + + return std::vector<char>(flatBufferBuilder.GetBufferPointer(), + flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); +} + +template <typename T> +void PackTest(tflite::BuiltinOperator packOperatorCode, + tflite::TensorType tensorType, + std::vector<armnn::BackendId>& backends, + std::vector<int32_t>& inputShape, + std::vector<int32_t>& expectedOutputShape, + std::vector<std::vector<T>>& inputValues, + std::vector<T>& expectedOutputValues, + unsigned int axis = 0, + float quantScale = 1.0f, + int quantOffset = 0) +{ + using namespace tflite; + std::vector<char> modelBuffer = CreatePackTfLiteModel(packOperatorCode, + tensorType, + inputShape, + expectedOutputShape, + inputValues.size(), + axis, + quantScale, + quantOffset); + + const Model* tfLiteModel = GetModel(modelBuffer.data()); + + // Create TfLite Interpreters + std::unique_ptr<Interpreter> armnnDelegateInterpreter; + CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver()) + (&armnnDelegateInterpreter) == kTfLiteOk); + CHECK(armnnDelegateInterpreter != nullptr); + CHECK(armnnDelegateInterpreter->AllocateTensors() == kTfLiteOk); + + std::unique_ptr<Interpreter> tfLiteInterpreter; + CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver()) + (&tfLiteInterpreter) == kTfLiteOk); + CHECK(tfLiteInterpreter != nullptr); + CHECK(tfLiteInterpreter->AllocateTensors() == kTfLiteOk); + + // Create the ArmNN Delegate + armnnDelegate::DelegateOptions delegateOptions(backends); + std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)> + theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions), + armnnDelegate::TfLiteArmnnDelegateDelete); + CHECK(theArmnnDelegate != nullptr); + + // Modify armnnDelegateInterpreter to use armnnDelegate + CHECK(armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk); + + // Set input data for all input tensors. + for (unsigned int i = 0; i < inputValues.size(); ++i) + { + // Get single input tensor and assign to interpreters. + auto inputTensorValues = inputValues[i]; + armnnDelegate::FillInput<T>(tfLiteInterpreter, i, inputTensorValues); + armnnDelegate::FillInput<T>(armnnDelegateInterpreter, i, inputTensorValues); + } + + // Run EnqueWorkload + CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); + CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); + + // Compare output data + armnnDelegate::CompareOutputData<T>(tfLiteInterpreter, + armnnDelegateInterpreter, + expectedOutputShape, + expectedOutputValues); + + armnnDelegateInterpreter.reset(nullptr); +} + +} // anonymous namespace
\ No newline at end of file |