SparseToDense.cpp

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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 "SparseToDense.h"
 
#include "Convert.h"
 
namespace tflchef
{
 
void TFliteOpSparseToDense::filler(const tflite::Operator *op, TFliteImport *import,
                                   tflchef::ModelRecipe *model_recipe) const
{
  // filler for Shape
  const auto &inputs = *op->inputs();
 
  const tflite::Tensor *output_shape_tensor = import->tensors()->Get(inputs[1]);
  assert(output_shape_tensor->type() == tflite::TensorType::TensorType_INT32);
  const tflite::Buffer *buffer = import->buffers()->Get(output_shape_tensor->buffer());
  auto vec = extract_buffer<int32_t>(buffer);
  import->set_tensor_filler(inputs[1], vec);
}
 
tflchef::Operation *TFliteOpSparseToDense::build(RecipeChefContext *ctx) const
{
  tflchef::Operation *operation = ctx->chefop;
  const tflite::Operator *op = ctx->tflop;
 
  auto op_params = op->builtin_options_as_SparseToDenseOptions();
  assert(op_params != nullptr);
 
  operation->set_type("SparseToDense");
 
  auto op_options = operation->mutable_sparse_to_dense_options();
 
  op_options->set_validate_indices(op_params->validate_indices());
 
  return operation;
}
 
} // namespace tflchef