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/*
* Copyright (c) 2018 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 "DepthwiseConv2D.h"
#include "Convert.h"
namespace tflchef
{
void TFliteOpDepthwiseConv2D::filler(const tflite::Operator *op, TFliteImport *import,
tflchef::ModelRecipe *model_recipe) const
{
const std::vector<int32_t> &inputs = as_index_vector(op->inputs());
bool hasBias = (inputs.size() == 3);
assert(inputs.size() == 2 || hasBias);
import->set_tensor_filler(inputs.at(1)); // kernel
if (hasBias)
import->set_tensor_filler(inputs.at(2)); // bias
}
tflchef::Operation *TFliteOpDepthwiseConv2D::build(const tflite::Operator *op, TFliteImport *import,
tflchef::ModelRecipe *model_recipe) const
{
auto op_params = op->builtin_options_as_DepthwiseConv2DOptions();
assert(op_params != nullptr);
auto operation = model_recipe->add_operation();
operation->set_type("DepthwiseConv2D");
auto op_options = operation->mutable_depthwiseconv2d_options();
op_options->set_activation(as_tflchef_activation(op_params->fused_activation_function()));
op_options->set_stride_h(op_params->stride_h());
op_options->set_stride_w(op_params->stride_w());
op_options->set_depth_multiplier(op_params->depth_multiplier());
// TODO support dilation
// op_params->dilation_w_factor()
// op_params->dilation_h_factor()
op_options->set_padding(as_tflchef_padding(op_params->padding()));
return operation;
}
} // namespace tflchef
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