inference-engine/thirdparty/clDNN/src/gpu/activation_gpu.cpp

   1 /*
   2 // Copyright (c) 2016 Intel Corporation
   3 //
   4 // Licensed under the Apache License, Version 2.0 (the "License");
   5 // you may not use this file except in compliance with the License.
   6 // You may obtain a copy of the License at
   7 //
   8 //      http://www.apache.org/licenses/LICENSE-2.0
   9 //
  10 // Unless required by applicable law or agreed to in writing, software
  11 // distributed under the License is distributed on an "AS IS" BASIS,
  12 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13 // See the License for the specific language governing permissions and
  14 // limitations under the License.
  15 */
  16
  17 #include "activation_inst.h"
  18 #include "primitive_gpu_base.h"
  19 #include "implementation_map.h"
  20 #include "error_handler.h"
  21 #include "kernel_selector_helper.h"
  22 #include "activation/activation_kernel_selector.h"
  23 #include "activation/activation_kernel_base.h"
  24 #include "api/CPP/activation.hpp"
  25
  26 namespace cldnn { namespace gpu {
  27
  28
  29 struct activation_gpu : typed_primitive_gpu_impl<activation>
  30 {
  31     using parent = typed_primitive_gpu_impl<activation>;
  32     using parent::parent;
  33
  34     virtual kernel::kernel_arguments_data get_arguments(typed_primitive_inst<activation>& instance, int32_t split) const override
  35     {
  36         kernel::kernel_arguments_data args = parent::get_arguments(instance, split);
  37
  38         if (_outer.is_parameterized())
  39         {
  40             args.slope = &instance.slope_memory();
  41         }
  42
  43         return args;
  44     }
  45
  46     static primitive_impl* create(const activation_node& arg)
  47     {
  48         auto activation_params = get_default_params<kernel_selector::activation_params>(arg);
  49         auto activation_optional_params = get_default_optional_params<kernel_selector::activation_optional_params>(arg.get_program());
  50
  51         convert_new_activation_func(arg.get_primitive(), activation_params.activation);
  52
  53         if (arg.is_parameterized())
  54         {
  55             const auto& slope_layout = arg.slope_input().get_output_layout();
  56             const auto& output_layout = arg.get_output_layout();
  57
  58             const auto params_num = kernel_selector::GetActivationAdditionalParamsNumber(activation_params.activation.function);
  59
  60             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");
  61
  62             activation_params.inputActivationParams.push_back(convert_data_tensor(slope_layout));
  63         }
  64
  65         auto& kernel_selector = kernel_selector::activation_kernel_selector::Instance();
  66         auto best_kernels = kernel_selector.GetBestKernels(activation_params, activation_optional_params);
  67         CLDNN_ERROR_BOOL(arg.id(), "Best_kernel.empty()", best_kernels.empty(), "Cannot find a proper kernel with this arguments");
  68
  69         auto activation = new activation_gpu(arg, best_kernels[0]);
  70
  71         return activation;
  72     };
  73 };
  74
  75
  76 namespace {
  77     struct attach {
  78         attach() {
  79             auto val_fw = activation_gpu::create;
  80
  81             implementation_map<activation>::add({
  82                 { std::make_tuple(engine_types::ocl, data_types::f32, format::yxfb), val_fw},
  83                 { std::make_tuple(engine_types::ocl, data_types::f16, format::yxfb), val_fw},
  84                 { std::make_tuple(engine_types::ocl, data_types::f32, format::bfyx), val_fw },
  85                 { std::make_tuple(engine_types::ocl, data_types::f16, format::bfyx), val_fw },
  86                 { std::make_tuple(engine_types::ocl, data_types::f32, format::byxf), val_fw },
  87                 { std::make_tuple(engine_types::ocl, data_types::f16, format::byxf), val_fw },
  88             });
  89         }
  90         ~attach() {}
  91     };
  92     attach attach_impl;
  93 }
  94 } }