//
// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//

#pragma once

#include <tensorflow/lite/interpreter.h>

#include <doctest/doctest.h>

namespace armnnDelegate
{

/// Can be used to assign input data from a vector to a model input.
/// Example usage can be found in ResizeTesthelper.hpp
template <typename T>
void FillInput(std::unique_ptr<tflite::Interpreter>& interpreter, int inputIndex, std::vector<T>& inputValues)
{
    auto tfLiteDelegateInputId = interpreter->inputs()[inputIndex];
    auto tfLiteDelageInputData = interpreter->typed_tensor<T>(tfLiteDelegateInputId);
    for (unsigned int i = 0; i < inputValues.size(); ++i)
    {
        tfLiteDelageInputData[i] = inputValues[i];
    }
}

// Can be used to compare data with a tolerance depending on their data type
void CompareData(float tensor1[], float tensor2[], size_t tensorSize);
void CompareData(int8_t tensor1[], int8_t tensor2[], size_t tensorSize);
void CompareData(uint8_t tensor1[], uint8_t tensor2[], size_t tensorSize);
void CompareData(int16_t tensor1[], int16_t tensor2[], size_t tensorSize);


// Can be used to compare the output tensor shape and values
// from armnnDelegateInterpreter and tfLiteInterpreter.
// Example usage can be found in ControlTestHelper.hpp
template <typename T>
void CompareOutputData(std::unique_ptr<tflite::Interpreter>& tfLiteInterpreter,
                       std::unique_ptr<tflite::Interpreter>& armnnDelegateInterpreter,
                       std::vector<int32_t>& expectedOutputShape,
                       std::vector<T>& expectedOutputValues)
{
    auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0];
    auto tfLiteDelegateOutputTensor = tfLiteInterpreter->tensor(tfLiteDelegateOutputId);
    auto tfLiteDelegateOutputData = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateOutputId);
    auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0];
    auto armnnDelegateOutputTensor = armnnDelegateInterpreter->tensor(armnnDelegateOutputId);
    auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateOutputId);

    for (size_t i = 0; i < expectedOutputShape.size(); i++)
    {
        CHECK(expectedOutputShape[i] == armnnDelegateOutputTensor->dims->data[i]);
        CHECK(tfLiteDelegateOutputTensor->dims->data[i] == expectedOutputShape[i]);
        CHECK(tfLiteDelegateOutputTensor->dims->data[i] == armnnDelegateOutputTensor->dims->data[i]);
    }

    armnnDelegate::CompareData(expectedOutputValues.data(), armnnDelegateOutputData    , expectedOutputValues.size());
    armnnDelegate::CompareData(tfLiteDelegateOutputData   , expectedOutputValues.data(), expectedOutputValues.size());
    armnnDelegate::CompareData(tfLiteDelegateOutputData   , armnnDelegateOutputData    , expectedOutputValues.size());
}

} // namespace armnnDelegate