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 "activation_inst.h"
  #include "primitive_gpu_base.h"
  #include "implementation_map.h"
  #include "error_handler.h"
  #include "kernel_selector_helper.h"
  #include "activation/activation_kernel_selector.h"
  #include "activation/activation_kernel_base.h"
  #include "api/CPP/activation.hpp"
  
  namespace cldnn { namespace gpu {
  
  
  struct activation_gpu : typed_primitive_gpu_impl<activation>
  {
      using parent = typed_primitive_gpu_impl<activation>;
      using parent::parent;
  
      virtual kernel::kernel_arguments_data get_arguments(typed_primitive_inst<activation>& instance, int32_t split) const override
      {
          kernel::kernel_arguments_data args = parent::get_arguments(instance, split);
          
          if (_outer.is_parameterized())
          {
              args.slope = &instance.slope_memory();
          }
  
          return args;
      }
  
      static primitive_impl* create(const activation_node& arg) 
      { 
          auto activation_params = get_default_params<kernel_selector::activation_params>(arg);
          auto activation_optional_params = get_default_optional_params<kernel_selector::activation_optional_params>(arg.get_program());
  
          convert_new_activation_func(arg.get_primitive(), activation_params.activation);
  
          if (arg.is_parameterized())
          {
              const auto& slope_layout = arg.slope_input().get_output_layout();
              const auto& output_layout = arg.get_output_layout();
  
              const auto params_num = kernel_selector::GetActivationAdditionalParamsNumber(activation_params.activation.function);
  
              CLDNN_ERROR_LESS_THAN(arg.id(), "Slope layout size count", slope_layout.size.count(), "output_layout.size.feature[0] * params_num", static_cast<size_t>(output_layout.size.feature[0] * params_num), "Error - not enough data inside additional params buffer");
              
              activation_params.inputActivationParams.push_back(convert_data_tensor(slope_layout));
          }
  
          auto& kernel_selector = kernel_selector::activation_kernel_selector::Instance();
          auto best_kernels = kernel_selector.GetBestKernels(activation_params, activation_optional_params);
          CLDNN_ERROR_BOOL(arg.id(), "Best_kernel.empty()", best_kernels.empty(), "Cannot find a proper kernel with this arguments");
  
          auto activation = new activation_gpu(arg, best_kernels[0]);
  
          return activation;
      };
  };
  
  
  namespace {
      struct attach {
          attach() {
              auto val_fw = activation_gpu::create;
      
              implementation_map<activation>::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;
  }
  } }
  