text: /*
  // Copyright (c) 2017-2018 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 "roi_pooling_inst.h"
  #include "primitive_gpu_base.h"
  #include "implementation_map.h"
  #include "error_handler.h"
  #include "kernel_selector_helper.h"
  #include "roi_pooling/roi_pooling_kernel_selector.h"
  #include "roi_pooling/roi_pooling_kernel_ref.h"
  
  namespace cldnn { namespace gpu {
  
  namespace {
      static inline bool hasSingleBatchOutput(const program_node & node)
      {
          const auto & batch = node.get_output_layout().size.batch;
  
          return batch.empty() || (batch.size() == 1 && batch[0] == 1);
      }
  
      kernel_selector::pool_type cldnn_2_pool_type(pooling_mode mode)
      {
          switch (mode)
          {
              case pooling_mode::max:
                  return kernel_selector::pool_type::MAX;
              case pooling_mode::average:
                  return kernel_selector::pool_type::AVG;
              case pooling_mode::average_no_padding:
                  return kernel_selector::pool_type::AVG;
              case pooling_mode::bilinear:
                  return kernel_selector::pool_type::BILINEAR;
              default:
                  assert(0);
                  return kernel_selector::pool_type::MAX;
          }
      }
  }
  
  
  struct roi_pooling_gpu : typed_primitive_gpu_impl<roi_pooling>
  {
      using parent = typed_primitive_gpu_impl<roi_pooling>;
      using parent::parent;
  
  protected:
  
      virtual kernel::kernel_arguments_data get_arguments(typed_primitive_inst<roi_pooling>& instance, int32_t) const override
      {
          kernel::kernel_arguments_data args;
  
          args.inputs = { &instance.input_memory(), &instance.rois_memory() };
          args.output = &instance.output_memory();
  
          return args;
      }
  
  public:
  
      static primitive_impl* create(const roi_pooling_node& arg)
      {
          const auto& input_layout    = arg.input().get_output_layout();
          const auto& output_layout   = arg.get_output_layout();
          const auto& rois_layout     = arg.rois().get_output_layout();
          const auto& primitive       = arg.get_primitive();
  
          const auto padding_filling_value = output_layout.data_padding.filling_value();
  
          CLDNN_ERROR_NOT_EQUAL(arg.id(), "roi_pooling padding filling value", padding_filling_value, "padding mode", 0.0f, "Unknown padding mode in roi_pooling.");
          CLDNN_ERROR_NOT_PROPER_FORMAT(arg.id(), "Input_layout.format", input_layout.format.value, "output_layout.format", output_layout.format);
  
          auto roi_params = get_default_params<kernel_selector::roi_pooling_params>(arg);
          auto roi_optional_params = get_default_optional_params<kernel_selector::roi_pooling_optional_params>(arg.get_program());
  
          const auto& out = roi_params.output;
  
          const auto roi_bfyx = convert_data_tensor(rois_layout);
          const auto roi_bf = roi_bfyx.FlattenFeatureAndSpatials();
          roi_params.inputs.push_back(roi_bf);
          roi_params.output = { out.GetDims(), out.GetDType(), kernel_selector::data_layout::brfyx, out.GetViewOffset(), out.PhysicalSize(), out.GetPaddedVal() }; // TOOD: it's an hack - cldnn doesn't support roi pooling with batching
          roi_params.mode               = cldnn_2_pool_type(primitive->mode);
          roi_params.position_sensitive = primitive->position_sensitive;
          roi_params.pooledWidth        = primitive->pooled_width;
          roi_params.pooledHeight       = primitive->pooled_height;
          roi_params.spatialScale       = primitive->spatial_scale;
          roi_params.spatial_bins_x     = primitive->spatial_bins_x;
          roi_params.spatial_bins_y     = primitive->spatial_bins_y;
  
          auto& kernel_selector = kernel_selector::roi_pooling_kernel_selector::Instance();
          auto best_kernels = kernel_selector.GetBestKernels(roi_params, roi_optional_params);
  
          CLDNN_ERROR_BOOL(arg.id(), "Best_kernel.empty()", best_kernels.empty(), "Cannot find a proper kernel with this arguments");
  
          auto roi_pool = new roi_pooling_gpu(arg, best_kernels[0]);
  
          return roi_pool;
      }
  };
  
  namespace {
      struct attach
      {
          attach()
          {
              implementation_map<roi_pooling>::add(std::make_tuple(engine_types::ocl, data_types::f16, format::bfyx), roi_pooling_gpu::create);
              implementation_map<roi_pooling>::add(std::make_tuple(engine_types::ocl, data_types::f32, format::bfyx), roi_pooling_gpu::create);
          }
  
          ~attach() {}
      };
  
      attach attach_impl;
  }
  } }
  