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/*
* Copyright (c) 2019 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 "interp/Registration.h"
namespace onert
{
namespace interp
{
namespace
{
void prepare(ExecEnv *env, const ir::Operation &node)
{
const auto in_index = node.getInputs().at(0);
const auto out_index = node.getOutputs().at(0);
// Unspecified shape is not supported in operation node spec now
const auto output_info = env->graph().operands().at(out_index).info();
env->allocateAndShareIfNeeded(out_index, output_info, in_index);
assert(output_info.total_size() == env->graph().operands().at(in_index).info().total_size());
}
void invoke(const ExecEnv *env, const ir::Operation &node)
{
const auto in_index = node.getInputs().at(0);
const auto out_index = node.getOutputs().at(0);
if (env->tensorAt(in_index)->bufferRO() == env->tensorAt(out_index)->bufferRO())
{
// Same data
return;
}
const auto output_info = env->graph().operands().at(out_index).info();
memcpy(env->tensorAt(out_index)->buffer(), env->tensorAt(in_index)->bufferRO(),
output_info.total_size());
}
} // namespace
OpKernel *getReshape()
{
static OpKernel kernel = {prepare, invoke};
return &kernel;
}
} // namespace interp
} // namespace onert
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