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 "Max.h"
  
  #include "ONNXHelpers.h"
  
  #include "mir/ops/MaxOp.h"
  
  namespace mir_onnx
  {
  
  static void convertMaxGeneric(const onnx::NodeProto &onnx_node, ConverterContext *context)
  {
    std::vector<mir::Operation::Output *> inputs = context->getNodeInputs(onnx_node);
    if (inputs.size() != 2)
    {
      throw std::runtime_error{"Unsupported number of inputs for Max operator"};
    }
    mir::Graph *graph = context->getGraph();
    auto result = createOp<mir::ops::MaxOp>(graph, inputs[0], inputs[1])->getOutput(0);
  
    context->setNodeOutputs(onnx_node, {result});
  }
  
  void convertMaxV1(const onnx::NodeProto &onnx_node, ConverterContext *context)
  {
    convertMaxGeneric(onnx_node, context);
  }
  
  void convertMaxV6(const onnx::NodeProto &onnx_node, ConverterContext *context)
  {
    convertMaxGeneric(onnx_node, context);
  }
  
  void convertMaxV8(const onnx::NodeProto &onnx_node, ConverterContext *context)
  {
    convertMaxGeneric(onnx_node, context);
  }
  
  } // namespace mir_onnx
  