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/*
* Copyright (c) 2022 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 "SVDF.h"
#include "Convert.h"
namespace tflchef
{
void TFliteOpSVDF::filler(const tflite::Operator *op, TFliteImport *import,
tflchef::ModelRecipe *model_recipe) const
{
const std::vector<int32_t> &inputs = as_index_vector(op->inputs());
assert(inputs.size() == 5);
// optional input tensor idx has minus value.
const bool hasBias = (inputs.at(3) >= 0);
// Note: last input is variable tensor without data
import->set_tensor_filler(inputs.at(1));
import->set_tensor_filler(inputs.at(2));
if (hasBias)
import->set_tensor_filler(inputs.at(3));
}
tflchef::Operation *TFliteOpSVDF::build(const tflite::Operator *op, TFliteImport *import,
tflchef::ModelRecipe *model_recipe) const
{
const auto op_params = op->builtin_options_as_SVDFOptions();
assert(op_params != nullptr);
auto operation = model_recipe->add_operation();
operation->set_type("SVDF");
auto op_options = operation->mutable_svdf_options();
op_options->set_activation(as_tflchef_activation(op_params->fused_activation_function()));
op_options->set_asymmetric_quantize_inputs(op_params->asymmetric_quantize_inputs());
op_options->set_rank(op_params->rank());
return operation;
}
} // namespace tflchef
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