text: /*
   * 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 "moco/Import/Nodes/StopGradient.h"
  
  #include <moco/IR/Nodes/TFStopGradient.h>
  
  #include <loco.h>
  #include <plier/tf/Convert.h>
  
  #include <memory>
  
  namespace
  {
  
  using namespace moco;
  
  /**
   * @brief GraphUpdate for TF StopGradient node
   */
  class TFStopGradientGraphUpdate final : public GraphUpdate
  {
  public:
    TFStopGradientGraphUpdate(TFStopGradient *node, TensorName &&name) : _node(node), _name(name) {}
  
    void input(const SymbolTable *) const override;
  
  private:
    TFStopGradient *_node;
    TensorName _name;
  };
  
  void TFStopGradientGraphUpdate::input(const SymbolTable *table) const
  {
    loco::Node *target = table->node(_name);
    _node->input(target);
  }
  
  } // namespace
  
  namespace moco
  {
  
  bool StopGradientGraphBuilder::validate(const tensorflow::NodeDef &node) const
  {
    if (node.input_size() != 1)
      return false;
  
    return plier::tf::has_attrs(node, {"T"});
  }
  
  void StopGradientGraphBuilder::build(const tensorflow::NodeDef &node,
                                       GraphBuilderContext *context) const
  {
    assert(context != nullptr);
  
    loco::Graph *graph = context->graph();
    SymbolTable *tensor_names = context->tensor_names();
    UpdateQueue *updates = context->updates();
  
    // creating TF dialect StopGradient node
    auto tf_stopgradient = graph->nodes()->create<TFStopGradient>();
    tf_stopgradient->name(node.name());
  
    // register string-name to node
    TensorName output_name(node.name(), 0);
    tensor_names->enroll(output_name, tf_stopgradient);
  
    // Queue node input update
    auto tf_stopgradient_update =
      std::make_unique<TFStopGradientGraphUpdate>(tf_stopgradient, TensorName(node.input(0)));
    updates->enroll(std::move(tf_stopgradient_update));
  }
  
  } // namespace moco
  