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//
// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ElementwiseUnaryTestHelper.hpp"
#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 armnnDelegate
{
TEST_SUITE("SqrtTest")
{
TEST_CASE ("SqrtTestFloat32")
{
using namespace tflite;
const std::vector<int32_t> inputShape { { 3, 1, 2} };
std::vector<char> modelBuffer = CreateElementwiseUnaryTfLiteModel(BuiltinOperator_SQRT,
::tflite::TensorType_FLOAT32,
inputShape);
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
auto delegateOptions = TfLiteArmnnDelegateOptionsDefault();
auto armnnDelegate = TfLiteArmnnDelegateCreate(delegateOptions);
CHECK(armnnDelegate != nullptr);
// Modify armnnDelegateInterpreter to use armnnDelegate
CHECK(armnnDelegateInterpreter->ModifyGraphWithDelegate(armnnDelegate) == kTfLiteOk);
// Set input data
std::vector<float> inputValues
{
9.0f, 4.25f, 81.9f,
0.1f, 0.9f, 169.0f
};
auto tfLiteDelegateInputId = tfLiteInterpreter->inputs()[0];
auto tfLiteDelageInputData = tfLiteInterpreter->typed_tensor<float>(tfLiteDelegateInputId);
for (unsigned int i = 0; i < inputValues.size(); ++i)
{
tfLiteDelageInputData[i] = inputValues[i];
}
auto armnnDelegateInputId = armnnDelegateInterpreter->inputs()[0];
auto armnnDelegateInputData = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateInputId);
for (unsigned int i = 0; i < inputValues.size(); ++i)
{
armnnDelegateInputData[i] = inputValues[i];
}
// Run EnqueWorkload
CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk);
CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
// Compare output data
auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0];
auto tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<float>(tfLiteDelegateOutputId);
auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0];
auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateOutputId);
for (size_t i = 0; i < inputValues.size(); i++)
{
CHECK(std::sqrt(inputValues[i]) == armnnDelegateOutputData[i]);
CHECK(tfLiteDelageOutputData[i] == armnnDelegateOutputData[i]);
}
}
}
} // namespace armnnDelegate
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