diff options
Diffstat (limited to 'delegate/test/ConvolutionTestHelper.hpp')
-rw-r--r-- | delegate/test/ConvolutionTestHelper.hpp | 225 |
1 files changed, 72 insertions, 153 deletions
diff --git a/delegate/test/ConvolutionTestHelper.hpp b/delegate/test/ConvolutionTestHelper.hpp index 2e211b2ee9..6a3400e9cb 100644 --- a/delegate/test/ConvolutionTestHelper.hpp +++ b/delegate/test/ConvolutionTestHelper.hpp @@ -8,6 +8,7 @@ #include "TestUtils.hpp" #include <armnn_delegate.hpp> +#include <DelegateTestInterpreter.hpp> #include <flatbuffers/flatbuffers.h> #include <tensorflow/lite/interpreter.h> @@ -186,7 +187,7 @@ std::vector<char> CreateConv2dTfLiteModel(tflite::BuiltinOperator convolutionOpe modelDescription, flatBufferBuilder.CreateVector(buffers.data(), buffers.size())); - flatBufferBuilder.Finish(flatbufferModel); + flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER); return std::vector<char>(flatBufferBuilder.GetBufferPointer(), flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); @@ -222,10 +223,9 @@ void ConvolutionTest(tflite::BuiltinOperator convolutionOperatorCode, int32_t filterQuantizationDim = 3) { - using namespace tflite; + using namespace delegateTestInterpreter; std::vector<char> modelBuffer; - modelBuffer = CreateConv2dTfLiteModel(convolutionOperatorCode, tensorType, strideX, @@ -251,59 +251,27 @@ void ConvolutionTest(tflite::BuiltinOperator convolutionOperatorCode, depth_multiplier, filterQuantizationDim); - - 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 - auto tfLiteDelegateInputId = tfLiteInterpreter->inputs()[0]; - auto tfLiteDelageInputData = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateInputId); - for (unsigned int i = 0; i < inputValues.size(); ++i) - { - tfLiteDelageInputData[i] = inputValues[i]; - } - - auto armnnDelegateInputId = armnnDelegateInterpreter->inputs()[0]; - auto armnnDelegateInputData = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateInputId); - for (unsigned int i = 0; i < inputValues.size(); ++i) - { - armnnDelegateInputData[i] = inputValues[i]; - } - // Run EnqueueWorkload - CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); - CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); - - // Compare output data - auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0]; - auto tfLiteDelagateOutputData = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateOutputId); - auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0]; - auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateOutputId); - for (size_t i = 0; i < expectedOutputValues.size(); i++) - { - CHECK(tfLiteDelagateOutputData[i] == armnnDelegateOutputData[i]); - CHECK(doctest::Approx(tfLiteDelagateOutputData[i]).epsilon(0.000001f) == expectedOutputValues[i]); - CHECK(doctest::Approx(armnnDelegateOutputData[i]).epsilon(0.000001f) == expectedOutputValues[i]); - } + // Setup interpreter with just TFLite Runtime. + auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer); + CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk); + CHECK(tfLiteInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk); + CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk); + std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(0); + std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0); + + // Setup interpreter with Arm NN Delegate applied. + auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends); + CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk); + CHECK(armnnInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk); + CHECK(armnnInterpreter.Invoke() == kTfLiteOk); + std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0); + std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0); + + armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues); + armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, outputShape); + + tfLiteInterpreter.Cleanup(); + armnnInterpreter.Cleanup(); } // Conv3d is only correctly supported for external delegates from TF Lite v2.6, as there was a breaking bug in v2.5. @@ -457,7 +425,7 @@ std::vector<char> CreateConv3dTfLiteModel(tflite::BuiltinOperator convolutionOpe modelDescription, flatBufferBuilder.CreateVector(buffers.data(), buffers.size())); - flatBufferBuilder.Finish(flatbufferModel); + flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER); return std::vector<char>(flatBufferBuilder.GetBufferPointer(), flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); @@ -490,7 +458,7 @@ void Convolution3dTest(tflite::BuiltinOperator convolutionOperatorCode, int32_t depth_multiplier = 1, int32_t filterQuantizationDim = 3) { - using namespace tflite; + using namespace delegateTestInterpreter; std::vector<char> modelBuffer; modelBuffer = CreateConv3dTfLiteModel(convolutionOperatorCode, @@ -516,48 +484,30 @@ void Convolution3dTest(tflite::BuiltinOperator convolutionOperatorCode, depth_multiplier, filterQuantizationDim); - 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 - armnnDelegate::FillInput<T>(tfLiteInterpreter, 0, inputValues); - armnnDelegate::FillInput<T>(armnnDelegateInterpreter, 0, inputValues); - - // Run EnqueueWorkload - CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); - CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); - - // Compare output data - auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0]; - auto tfLiteDelagateOutputData = tfLiteInterpreter->typed_tensor<float>(tfLiteDelegateOutputId); - auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0]; - auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateOutputId); - - armnnDelegate::CompareData(expectedOutputValues.data(), armnnDelegateOutputData, expectedOutputValues.size(), 1); - armnnDelegate::CompareData(expectedOutputValues.data(), tfLiteDelagateOutputData, expectedOutputValues.size(), 1); - armnnDelegate::CompareData(tfLiteDelagateOutputData, armnnDelegateOutputData, expectedOutputValues.size(), 1); + // Setup interpreter with just TFLite Runtime. + auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer); + CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk); + CHECK(tfLiteInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk); + CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk); + std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(0); + std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0); + + // Setup interpreter with Arm NN Delegate applied. + auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends); + CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk); + CHECK(armnnInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk); + CHECK(armnnInterpreter.Invoke() == kTfLiteOk); + std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0); + std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0); + + armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, outputShape); + + armnnDelegate::CompareData(expectedOutputValues.data(), armnnOutputValues.data(), expectedOutputValues.size(), 1); + armnnDelegate::CompareData(expectedOutputValues.data(), tfLiteOutputValues.data(), expectedOutputValues.size(), 1); + armnnDelegate::CompareData(tfLiteOutputValues.data(), armnnOutputValues.data(), expectedOutputValues.size(), 1); + + tfLiteInterpreter.Cleanup(); + armnnInterpreter.Cleanup(); } #endif @@ -675,7 +625,7 @@ std::vector<char> CreateTransposeConvTfLiteModel(tflite::TensorType tensorType, modelDescription, flatBufferBuilder.CreateVector(buffers.data(), buffers.size())); - flatBufferBuilder.Finish(flatbufferModel); + flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER); return std::vector<char>(flatBufferBuilder.GetBufferPointer(), flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); @@ -702,7 +652,7 @@ void TransposeConvTest(std::vector<armnn::BackendId>& backends, float quantScale = 1.0f, int quantOffset = 0) { - using namespace tflite; + using namespace delegateTestInterpreter; std::vector<char> modelBuffer; modelBuffer = CreateTransposeConvTfLiteModel<T>(tensorType, @@ -723,58 +673,27 @@ void TransposeConvTest(std::vector<armnn::BackendId>& backends, 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 - auto tfLiteDelegateInputId = tfLiteInterpreter->inputs()[2]; - auto tfLiteDelageInputData = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateInputId); - for (unsigned int i = 0; i < inputValues.size(); ++i) - { - tfLiteDelageInputData[i] = inputValues[i]; - } + // Setup interpreter with just TFLite Runtime. + auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer); + CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk); + CHECK(tfLiteInterpreter.FillInputTensor<T>(inputValues, 2) == kTfLiteOk); + CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk); + std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(0); + std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0); - auto armnnDelegateInputId = armnnDelegateInterpreter->inputs()[2]; - auto armnnDelegateInputData = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateInputId); - for (unsigned int i = 0; i < inputValues.size(); ++i) - { - armnnDelegateInputData[i] = inputValues[i]; - } - // Run EnqueueWorkload - CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); - CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); - - // Compare output data - auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0]; - auto tfLiteDelagateOutputData = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateOutputId); - auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0]; - auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateOutputId); - for (size_t i = 0; i < expectedOutputValues.size(); i++) - { - CHECK(armnnDelegateOutputData[i] == expectedOutputValues[i]); - CHECK(tfLiteDelagateOutputData[i] == expectedOutputValues[i]); - CHECK(tfLiteDelagateOutputData[i] == armnnDelegateOutputData[i]); - } + // Setup interpreter with Arm NN Delegate applied. + auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends); + CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk); + CHECK(armnnInterpreter.FillInputTensor<T>(inputValues, 2) == kTfLiteOk); + CHECK(armnnInterpreter.Invoke() == kTfLiteOk); + std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0); + std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0); + + armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues); + armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, outputTensorShape); + + tfLiteInterpreter.Cleanup(); + armnnInterpreter.Cleanup(); } } // anonymous namespace |