text: //*****************************************************************************
  // Copyright 2017-2020 Intel Corporation
  //
  // 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.
  //*****************************************************************************
  
  #pragma once
  
  #include <string>
  #include <vector>
  
  #include "gpu_compiled_function.hpp"
  #include "gpu_tensor_wrapper.hpp"
  #include "ngraph/node.hpp"
  
  namespace ngraph
  {
      namespace runtime
      {
          namespace gpu
          {
              class GPU_Emitter
              {
              public:
                  static std::function<std::string(EMIT_ARGS)> get_emit_function(const Node& node);
  
  // This defines a collection of function declarations like this
  // static std::string emit_Abs(EMIT_ARGS);
  // static std::string emit_Acos(EMIT_ARGS);
  #define NGRAPH_OP(OP, NAMESPACE) static std::string emit_##OP(EMIT_ARGS);
  #include "op/op_tbl.hpp"
  #undef NGRAPH_OP
  
                  template <typename T>
                  static std::string emit_elementwise(EMIT_ARGS)
                  {
                      if (out[0].get_size() == 0)
                      {
                          return "";
                      }
                      else if (out.size() > 1)
                      {
                          throw std::runtime_error(
                              "Multi-output elementwise ops are not currently supported.");
                      }
                      auto& cuda_emitter =
                          compiled_function->get_primitive_emitter()->get_cuda_emitter();
  
                      std::vector<std::string> dtypes;
                      for (auto& arg : args)
                      {
                          dtypes.push_back(arg.get_type());
                      }
                      // Special case for bool data type.
                      if (out[0].get_element_type() == element::boolean)
                      {
                          dtypes.push_back("bool");
                      }
                      else
                      {
                          dtypes.push_back(out[0].get_type());
                      }
                      auto ew_index = cuda_emitter->build_elementwise<T>(dtypes, out[0].get_shape());
  
                      return compiled_function->add_to_runtime(ew_index, function_name, args, out);
                  }
  
                  static std::string emit_ArgReduce(EMIT_ARGS, cudnnReduceTensorOp_t);
                  static std::string emit_Sum_0(EMIT_ARGS);
                  static std::string emit_Sum_1(EMIT_ARGS);
  
                  /// \brief Create a list of node names for each arg in args
                  /// \param args list of tensor arguments
                  /// \param arg_indexes a list of indexes into args for which args to include in
                  ///    the output list, so {1, 2} will include args 1 and 2 and skip 0.
                  /// \ return returns a string containing "arg0_name, arg1_name, etc."
                  static std::string node_names(const std::vector<GPUTensorWrapper>& args,
                                                std::initializer_list<int> arg_indexes = {});
              };
  
              Shape get_padded_shape(const Shape& input_shape,
                                     const Shape& padding_below,
                                     const Shape& padding_above,
                                     const Shape& padding_interior);
          }
      }
  }
  