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//
// Copyright © 2020, 2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "TestUtils.hpp"
#include <armnn_delegate.hpp>
#include <DelegateTestInterpreter.hpp>
#include <flatbuffers/flatbuffers.h>
#include <tensorflow/lite/kernels/register.h>
#include <tensorflow/lite/version.h>
#include <schema_generated.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));
buffers.push_back(CreateBuffer(flatBufferBuilder));
buffers.push_back(CreateBuffer(flatBufferBuilder));
buffers.push_back(CreateBuffer(flatBufferBuilder));
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,
1,
flatBufferBuilder.CreateString("input_0"),
quantizationParameters);
tensors[1] = CreateTensor(flatBufferBuilder,
flatBufferBuilder.CreateVector<int32_t>(input1TensorShape.data(),
input1TensorShape.size()),
tensorType,
2,
flatBufferBuilder.CreateString("input_1"),
quantizationParameters);
tensors[2] = CreateTensor(flatBufferBuilder,
flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
outputTensorShape.size()),
::tflite::TensorType_BOOL,
3);
// 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, armnnDelegate::FILE_IDENTIFIER);
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 delegateTestInterpreter;
std::vector<char> modelBuffer = CreateComparisonTfLiteModel(comparisonOperatorCode,
tensorType,
input0Shape,
input1Shape,
outputShape,
quantScale,
quantOffset);
// Setup interpreter with just TFLite Runtime.
auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
CHECK(tfLiteInterpreter.FillInputTensor<T>(input0Values, 0) == kTfLiteOk);
CHECK(tfLiteInterpreter.FillInputTensor<T>(input1Values, 1) == kTfLiteOk);
CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
std::vector<bool> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult(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>(input0Values, 0) == kTfLiteOk);
CHECK(armnnInterpreter.FillInputTensor<T>(input1Values, 1) == kTfLiteOk);
CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
std::vector<bool> armnnOutputValues = armnnInterpreter.GetOutputResult(0);
std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0);
armnnDelegate::CompareData(expectedOutputValues, armnnOutputValues, expectedOutputValues.size());
armnnDelegate::CompareData(expectedOutputValues, tfLiteOutputValues, expectedOutputValues.size());
armnnDelegate::CompareData(tfLiteOutputValues, armnnOutputValues, expectedOutputValues.size());
armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, outputShape);
tfLiteInterpreter.Cleanup();
armnnInterpreter.Cleanup();
}
} // anonymous namespace
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