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/*
* Copyright (c) 2020 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 "Pad.h"
#include "Convert.h"
namespace tflchef
{
void TFliteOpPad::filler(const tflite::Operator *op, TFliteImport *import,
tflchef::ModelRecipe *model_recipe) const
{
// filler for second input
const auto &inputs = *op->inputs();
const tflite::Tensor *tensor = import->tensors()->Get(inputs[1]);
assert(tensor->type() == tflite::TensorType::TensorType_INT32);
const tflite::Buffer *buffer = import->buffers()->Get(tensor->buffer());
auto vec = extract_buffer<int32_t>(buffer);
import->set_tensor_filler(inputs[1], vec);
}
tflchef::Operation *TFliteOpPad::build(const tflite::Operator *op, TFliteImport *import,
tflchef::ModelRecipe *model_recipe) const
{
auto operation = model_recipe->add_operation();
operation->set_type("Pad");
return operation;
}
} // namespace tflchef
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