text: /*
  // Copyright (c) 2016 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.
  */
  
  #include "fully_connected_grad_input_inst.h"
  #include "primitive_gpu_base.h"
  #include "implementation_map.h"
  #include "error_handler.h"
  #include "kernel_selector_helper.h"
  #include "api/CPP/fully_connected_grad_input.hpp"
  
  namespace cldnn { namespace gpu {
  
  struct fully_connected_grad_input_gpu : typed_primitive_gpu_impl<fully_connected_grad_input>
  {
      using parent = typed_primitive_gpu_impl<fully_connected_grad_input>;
      using parent::parent;
  
  protected:
  
      virtual kernel::kernel_arguments_data get_arguments(typed_primitive_inst<fully_connected_grad_input>& instance, int32_t) const override
      {
          kernel::kernel_arguments_data args = parent::get_arguments(instance, 1);
          args.weights = &instance.weights_memory();
  
          return args;
      }
  
  public:
  
      static primitive_impl* create(const fully_connected_grad_input_node& arg)
      {
          auto fully_connected_grad_input_params = get_default_params<kernel_selector::fully_connected_grad_input_params>(arg);
          auto fully_connected_grad_input_optional_params = get_default_optional_params<kernel_selector::fully_connected_grad_input_optional_params>(arg.get_program());
  
          const auto& weights_layout = arg.weights().get_output_layout();
          fully_connected_grad_input_params.weights = convert_weights_tensor(weights_layout);
          fully_connected_grad_input_params.gradient = true;
          fully_connected_grad_input_params.inputs.push_back(convert_data_tensor(arg.get_dependency(1).get_output_layout()));
  
          auto& kernel_selector = kernel_selector::fully_connected_grad_input_kernel_selector::Instance();
          auto best_kernels = kernel_selector.GetBestKernels(fully_connected_grad_input_params, fully_connected_grad_input_optional_params);
          CLDNN_ERROR_BOOL(arg.id(), "Best_kernel.empty()", best_kernels.empty(), "Cannot find a proper kernel with this arguments");
  
          auto fully_connected_grad_input = new fully_connected_grad_input_gpu(arg, best_kernels[0]);
  
          return fully_connected_grad_input;
      };
  };
  
  
  namespace {
      struct attach {
          attach() {
              auto val_fw = fully_connected_grad_input_gpu::create;
  
              implementation_map<fully_connected_grad_input>::add({
                  { std::make_tuple(engine_types::ocl, data_types::f32, format::yxfb), val_fw },
                  { std::make_tuple(engine_types::ocl, data_types::f16, format::yxfb), val_fw },
                  { std::make_tuple(engine_types::ocl, data_types::f32, format::bfyx), val_fw },
                  { std::make_tuple(engine_types::ocl, data_types::f16, format::bfyx), val_fw },
                  { std::make_tuple(engine_types::ocl, data_types::f32, format::byxf), val_fw },
                  { std::make_tuple(engine_types::ocl, data_types::f16, format::byxf), val_fw },
              });
          }
          ~attach() {}
      };
      attach attach_impl;
  }
  } }