diff options
author | Sadik Armagan <sadik.armagan@arm.com> | 2020-11-09 08:26:22 +0000 |
---|---|---|
committer | Sadik Armagan <sadik.armagan@arm.com> | 2020-11-10 15:08:17 +0000 |
commit | 8b9858d891439fd1b0710e5d245e2116a3b88d30 (patch) | |
tree | 744f81bd24a172800f2fdbfe425550a68824e978 /delegate/src/test/ComparisonTestHelper.hpp | |
parent | 21a94ff6212aac28398f90373e873d43390070a3 (diff) | |
download | armnn-8b9858d891439fd1b0710e5d245e2116a3b88d30.tar.gz |
IVGCVSW-5380 'TfLiteDelegate: Implement the Comparison operators'
* Implemented Comparison Operators
* Added unit tests
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: Icdc0f7c6a286a8364a2770b26d15e8958291dc2b
Diffstat (limited to 'delegate/src/test/ComparisonTestHelper.hpp')
-rw-r--r-- | delegate/src/test/ComparisonTestHelper.hpp | 236 |
1 files changed, 236 insertions, 0 deletions
diff --git a/delegate/src/test/ComparisonTestHelper.hpp b/delegate/src/test/ComparisonTestHelper.hpp new file mode 100644 index 0000000000..0011c763a0 --- /dev/null +++ b/delegate/src/test/ComparisonTestHelper.hpp @@ -0,0 +1,236 @@ +// +// Copyright © 2020 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> CreateComparisonTfLiteModel(tflite::BuiltinOperator comparisonOperatorCode, + tflite::TensorType tensorType, + const std::vector <int32_t>& input0TensorShape, + const std::vector <int32_t>& input1TensorShape, + const std::vector <int32_t>& outputTensorShape, + 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::array<flatbuffers::Offset<Tensor>, 3> tensors; + tensors[0] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(input0TensorShape.data(), + input0TensorShape.size()), + tensorType, + 0, + flatBufferBuilder.CreateString("input_0"), + quantizationParameters); + tensors[1] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(input1TensorShape.data(), + input1TensorShape.size()), + tensorType, + 0, + flatBufferBuilder.CreateString("input_1"), + quantizationParameters); + tensors[2] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), + outputTensorShape.size()), + ::tflite::TensorType_BOOL, + 0); + + // create operator + tflite::BuiltinOptions operatorBuiltinOptionsType = BuiltinOptions_EqualOptions;; + flatbuffers::Offset<void> operatorBuiltinOptions = CreateEqualOptions(flatBufferBuilder).Union(); + switch (comparisonOperatorCode) + { + case BuiltinOperator_EQUAL: + { + operatorBuiltinOptionsType = BuiltinOptions_EqualOptions; + operatorBuiltinOptions = CreateEqualOptions(flatBufferBuilder).Union(); + break; + } + case BuiltinOperator_NOT_EQUAL: + { + operatorBuiltinOptionsType = BuiltinOptions_NotEqualOptions; + operatorBuiltinOptions = CreateNotEqualOptions(flatBufferBuilder).Union(); + break; + } + case BuiltinOperator_GREATER: + { + operatorBuiltinOptionsType = BuiltinOptions_GreaterOptions; + operatorBuiltinOptions = CreateGreaterOptions(flatBufferBuilder).Union(); + break; + } + case BuiltinOperator_GREATER_EQUAL: + { + operatorBuiltinOptionsType = BuiltinOptions_GreaterEqualOptions; + operatorBuiltinOptions = CreateGreaterEqualOptions(flatBufferBuilder).Union(); + break; + } + case BuiltinOperator_LESS: + { + operatorBuiltinOptionsType = BuiltinOptions_LessOptions; + operatorBuiltinOptions = CreateLessOptions(flatBufferBuilder).Union(); + break; + } + case BuiltinOperator_LESS_EQUAL: + { + operatorBuiltinOptionsType = BuiltinOptions_LessEqualOptions; + operatorBuiltinOptions = CreateLessEqualOptions(flatBufferBuilder).Union(); + break; + } + default: + break; + } + const std::vector<int32_t> operatorInputs{ {0, 1} }; + const std::vector<int32_t> operatorOutputs{{2}}; + flatbuffers::Offset <Operator> comparisonOperator = + CreateOperator(flatBufferBuilder, + 0, + flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), + flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), + operatorBuiltinOptionsType, + operatorBuiltinOptions); + + 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(&comparisonOperator, 1)); + + flatbuffers::Offset <flatbuffers::String> modelDescription = + flatBufferBuilder.CreateString("ArmnnDelegate: Comparison Operator Model"); + flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, comparisonOperatorCode); + + 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 ComparisonTest(tflite::BuiltinOperator comparisonOperatorCode, + tflite::TensorType tensorType, + std::vector<armnn::BackendId>& backends, + std::vector<int32_t>& input0Shape, + std::vector<int32_t>& input1Shape, + std::vector<int32_t>& outputShape, + std::vector<T>& input0Values, + std::vector<T>& input1Values, + std::vector<bool>& expectedOutputValues, + float quantScale = 1.0f, + int quantOffset = 0) +{ + using namespace tflite; + std::vector<char> modelBuffer = CreateComparisonTfLiteModel(comparisonOperatorCode, + tensorType, + input0Shape, + input1Shape, + outputShape, + 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 + auto tfLiteDelegateInput0Id = tfLiteInterpreter->inputs()[0]; + auto tfLiteDelageInput0Data = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateInput0Id); + for (unsigned int i = 0; i < input0Values.size(); ++i) + { + tfLiteDelageInput0Data[i] = input0Values[i]; + } + + auto tfLiteDelegateInput1Id = tfLiteInterpreter->inputs()[1]; + auto tfLiteDelageInput1Data = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateInput1Id); + for (unsigned int i = 0; i < input1Values.size(); ++i) + { + tfLiteDelageInput1Data[i] = input1Values[i]; + } + + auto armnnDelegateInput0Id = armnnDelegateInterpreter->inputs()[0]; + auto armnnDelegateInput0Data = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateInput0Id); + for (unsigned int i = 0; i < input0Values.size(); ++i) + { + armnnDelegateInput0Data[i] = input0Values[i]; + } + + auto armnnDelegateInput1Id = armnnDelegateInterpreter->inputs()[1]; + auto armnnDelegateInput1Data = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateInput1Id); + for (unsigned int i = 0; i < input1Values.size(); ++i) + { + armnnDelegateInput1Data[i] = input1Values[i]; + } + + // Run EnqueWorkload + CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); + CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); + // Compare output data + auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0]; + auto tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<bool>(tfLiteDelegateOutputId); + auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0]; + auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<bool>(armnnDelegateOutputId); + + for (size_t i = 0; i < expectedOutputValues.size(); i++) + { + CHECK(expectedOutputValues[i] == armnnDelegateOutputData[i]); + CHECK(tfLiteDelageOutputData[i] == expectedOutputValues[i]); + CHECK(tfLiteDelageOutputData[i] == armnnDelegateOutputData[i]); + } +} + +} // anonymous namespace
\ No newline at end of file |