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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 "NonMaxSuppressionV5.h"
#include "Convert.h"
#include "FillerHelper.h"
namespace tflchef
{
void TFliteOpNonMaxSuppressionV5::filler(const tflite::Operator *op, TFliteImport *import,
tflchef::ModelRecipe *model_recipe) const
{
const auto &inputs = *op->inputs();
const tflite::Tensor *max_output_size_tensor = import->tensors()->Get(inputs[2]);
assert(max_output_size_tensor->type() == tflite::TensorType::TensorType_INT32);
const tflite::Tensor *iou_threshold_tensor = import->tensors()->Get(inputs[3]);
assert(iou_threshold_tensor->type() == tflite::TensorType::TensorType_FLOAT32);
const tflite::Tensor *score_threshold_tensor = import->tensors()->Get(inputs[4]);
assert(score_threshold_tensor->type() == tflite::TensorType::TensorType_FLOAT32);
const tflite::Tensor *soft_nms_sigma_tensor = import->tensors()->Get(inputs[5]);
assert(soft_nms_sigma_tensor->type() == tflite::TensorType::TensorType_FLOAT32);
for (int32_t index = 2; index < 6; ++index)
{
fill_tensor_to_import(index, import);
}
}
tflchef::Operation *TFliteOpNonMaxSuppressionV5::build(const tflite::Operator *op,
TFliteImport *import,
tflchef::ModelRecipe *model_recipe) const
{
auto operation = model_recipe->add_operation();
operation->set_type("NonMaxSuppressionV5");
return operation;
}
} // namespace tflchef
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