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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 "Scale.h"
#include "ONNXHelpers.h"
#include "mir/ops/ConstantOp.h"
#include "mir/ops/ScaleOp.h"
namespace mir_onnx
{
std::vector<mir::Operation::Output *>
ScaleNodeConverter::convert(const onnx::NodeProto &onnx_node,
const std::vector<mir::Operation::Output *> &inputs,
mir::Graph *graph) const
{
bool found;
float value;
std::tie(found, value) = getFloatAttribute(onnx_node, "scale");
float scale_val = found ? value : 1.0;
const auto &shape = inputs[0]->getShape();
auto scale_tensor = createScalarTensor(scale_val, shape);
auto scale = createOp<mir::ops::ConstantOp>(graph, scale_tensor)->getOutput(0);
auto result = createOp<mir::ops::ScaleOp>(graph, inputs[0], scale);
return {result->getOutput(0)};
}
} // namespace mir_onnx
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