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/*
* Copyright (c) 2021 Samsung Electronics Co., Ltd. All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "tflite/RandomInputInitializer.h"
#include "tflite/TensorView.h"
#include <misc/tensor/IndexIterator.h>
namespace nnfw
{
namespace tflite
{
namespace
{
template <typename T>
void setValue(nnfw::misc::RandomGenerator &randgen, const TfLiteTensor *tensor)
{
auto tensor_view = nnfw::tflite::TensorView<T>::make(tensor);
nnfw::misc::tensor::iterate(tensor_view.shape())
<< [&](const nnfw::misc::tensor::Index &ind) { tensor_view.at(ind) = randgen.generate<T>(); };
}
} // namespace
void RandomInputInitializer::run(TfLiteInterpreter &interp)
{
const auto input_count = TfLiteInterpreterGetInputTensorCount(&interp);
for (int32_t idx = 0; idx < input_count; idx++)
{
auto tensor = TfLiteInterpreterGetInputTensor(&interp, idx);
auto const tensor_type = TfLiteTensorType(tensor);
switch (tensor_type)
{
case kTfLiteFloat32:
setValue<float>(_randgen, tensor);
break;
case kTfLiteInt32:
setValue<int32_t>(_randgen, tensor);
break;
case kTfLiteUInt8:
setValue<uint8_t>(_randgen, tensor);
break;
case kTfLiteBool:
setValue<bool>(_randgen, tensor);
break;
case kTfLiteInt8:
setValue<int8_t>(_randgen, tensor);
break;
default:
throw std::runtime_error{"Not supported input type"};
}
}
}
} // namespace tflite
} // namespace nnfw
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