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Diffstat (limited to 'delegate/src/test/TransposeTestHelper.hpp')
| -rw-r--r-- | delegate/src/test/TransposeTestHelper.hpp | 177 |
1 files changed, 0 insertions, 177 deletions
diff --git a/delegate/src/test/TransposeTestHelper.hpp b/delegate/src/test/TransposeTestHelper.hpp deleted file mode 100644 index 4479c486cb..0000000000 --- a/delegate/src/test/TransposeTestHelper.hpp +++ /dev/null @@ -1,177 +0,0 @@ -// -// Copyright © 2020, 2023 Arm Ltd and Contributors. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#pragma once - -#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> - -namespace -{ -std::vector<char> CreateTransposeTfLiteModel(tflite::TensorType tensorType, - const std::vector <int32_t>& input0TensorShape, - const std::vector <int32_t>& inputPermVecShape, - const std::vector <int32_t>& outputTensorShape, - const std::vector<int32_t>& inputPermVec) -{ - using namespace tflite; - flatbuffers::FlatBufferBuilder flatBufferBuilder; - flatbuffers::Offset<tflite::Buffer> buffers[4]{ - CreateBuffer(flatBufferBuilder), - CreateBuffer(flatBufferBuilder), - CreateBuffer(flatBufferBuilder, - flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(inputPermVec.data()), - sizeof(int32_t) * inputPermVec.size())), - CreateBuffer(flatBufferBuilder) - }; - std::array<flatbuffers::Offset<Tensor>, 3> tensors; - tensors[0] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(input0TensorShape.data(), - input0TensorShape.size()), - tensorType, 1); - tensors[1] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(inputPermVecShape.data(), - inputPermVecShape.size()), - tflite::TensorType_INT32, 2, - flatBufferBuilder.CreateString("permutation_vector")); - tensors[2] = CreateTensor(flatBufferBuilder, - flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), - outputTensorShape.size()), - tensorType,3); - const std::vector<int32_t> operatorInputs{0, 1}; - const std::vector<int32_t> operatorOutputs{2}; - flatbuffers::Offset <Operator> transposeOperator = - CreateOperator(flatBufferBuilder, - 0, - flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), - flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), - BuiltinOptions_TransposeOptions, - CreateTransposeOptions(flatBufferBuilder).Union()); - const std::vector<int> subgraphInputs{0, 1}; - const std::vector<int> subgraphOutputs{2}; - 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(&transposeOperator, 1)); - flatbuffers::Offset <flatbuffers::String> modelDescription = - flatBufferBuilder.CreateString("ArmnnDelegate: Transpose Operator Model"); - flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, - tflite::BuiltinOperator_TRANSPOSE); - flatbuffers::Offset <Model> flatbufferModel = - CreateModel(flatBufferBuilder, - TFLITE_SCHEMA_VERSION, - flatBufferBuilder.CreateVector(&operatorCode, 1), - flatBufferBuilder.CreateVector(&subgraph, 1), - modelDescription, - flatBufferBuilder.CreateVector(buffers, 4)); - flatBufferBuilder.Finish(flatbufferModel); - return std::vector<char>(flatBufferBuilder.GetBufferPointer(), - flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); -} - -void TransposeFP32Test(std::vector<armnn::BackendId>& backends) -{ - using namespace tflite; - - // set test input data - std::vector<int32_t> input0Shape {4, 2, 3}; - std::vector<int32_t> inputPermVecShape {3}; - std::vector<int32_t> outputShape {2, 3, 4}; - - std::vector<float> input0Values = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, - 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}; - std::vector<int32_t> inputPermVec = {2, 0, 1}; - std::vector<float> expectedOutputValues = {0, 3, 6, 9, 12, 15, 18, 21, 1, 4, 7, 10, - 13, 16, 19, 22, 2, 5, 8, 11, 14, 17, 20, 23}; - - // create model - std::vector<char> modelBuffer = CreateTransposeTfLiteModel(::tflite::TensorType_FLOAT32, - input0Shape, - inputPermVecShape, - outputShape, - inputPermVec); - - 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 tflite - auto tfLiteInterpreterInput0Id = tfLiteInterpreter->inputs()[0]; - auto tfLiteInterpreterInput0Data = tfLiteInterpreter->typed_tensor<float>(tfLiteInterpreterInput0Id); - for (unsigned int i = 0; i < input0Values.size(); ++i) - { - tfLiteInterpreterInput0Data[i] = input0Values[i]; - } - - auto tfLiteInterpreterInput1Id = tfLiteInterpreter->inputs()[1]; - auto tfLiteInterpreterInput1Data = tfLiteInterpreter->typed_tensor<int32_t>(tfLiteInterpreterInput1Id); - for (unsigned int i = 0; i < inputPermVec.size(); ++i) - { - tfLiteInterpreterInput1Data[i] = inputPermVec[i]; - } - - //Set input data for armnn delegate - auto armnnDelegateInput0Id = armnnDelegateInterpreter->inputs()[0]; - auto armnnDelegateInput0Data = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateInput0Id); - for (unsigned int i = 0; i < input0Values.size(); ++i) - { - armnnDelegateInput0Data[i] = input0Values[i]; - } - - auto armnnDelegateInput1Id = armnnDelegateInterpreter->inputs()[1]; - auto armnnDelegateInput1Data = armnnDelegateInterpreter->typed_tensor<int32_t>(armnnDelegateInput1Id); - for (unsigned int i = 0; i < inputPermVec.size(); ++i) - { - armnnDelegateInput1Data[i] = inputPermVec[i]; - } - - // Run EnqueWorkload - CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); - CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); - - // Compare output data - auto tfLiteInterpreterOutputId = tfLiteInterpreter->outputs()[0]; - auto tfLiteInterpreterOutputData = tfLiteInterpreter->typed_tensor<float>(tfLiteInterpreterOutputId); - auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0]; - auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateOutputId); - for (size_t i = 0; i < expectedOutputValues.size(); ++i) - { - CHECK(expectedOutputValues[i] == armnnDelegateOutputData[i]); - CHECK(tfLiteInterpreterOutputData[i] == expectedOutputValues[i]); - CHECK(tfLiteInterpreterOutputData[i] == armnnDelegateOutputData[i]); - } - - armnnDelegateInterpreter.reset(nullptr); -} -} |