inference-engine/thirdparty/clDNN/kernel_selector/core/actual_kernels/convolution/convolution_kernel_selector.cpp

   1 /*
   2 // Copyright (c) 2016-2018 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 "convolution_kernel_selector.h"
  18 #include "convolution_kernel_bfyx_ref.h"
  19 #include "convolution_kernel_bfyx_1x1_opt.h"
  20 #include "convolution_kernel_bfyx_gemm_like.h"
  21 #include "convolution_kernel_bfyx_direct_10_12_16.h"
  22 #include "convolution_kernel_bfyx_os_iyx_osv16.h"
  23 #include "convolution_kernel_bfyx_os_iyx_osv16_2_sg.h"
  24 #include "convolution_kernel_yxfb_ref.h"
  25 #include "convolution_kernel_yxfb_yxio_b16.h"
  26 #include "convolution_kernel_yxfb_yxio_b8.h"
  27 #include "convolution_kernel_yxfb_yxio_b1_block.h"
  28 #include "convolution_kernel_yxfb_yxio_b1_block_multiple_x.h"
  29 #include "convolution_kernel_tutorial.h"
  30 //#include "convolution_kernel_bfyx_3x3_dw_opt.h"
  31 #include "convolution_kernel_winograd_2x3_s1.h"
  32 #include "convolution_kernel_bfyx_1x1.h"
  33 #include "convolution_kernel_bfyx_1x1_gemm_buf.h"
  34 #include "convolution_kernel_winograd_2x3_s1_fused.h"
  35 #include "convolution_kernel_winograd_6x3_s1_fused.h"
  36 #include "convolution_kernel_MMAD.h"
  37 #include "convolution_kernel_MMAD_blocks.h"
  38 #include "convolution_kernel_1x1_gemm_MMAD.h"
  39 #include "convolution_kernel_byxf_af32_depthwise.h"
  40 #include "convolution_kernel_mmad_batched.h"
  41 #include "convolution_kernel_bfyx_depthwise_weights_lwg.h"
  42 #include "convolution_kernel_mmad_slm_2x14_rep4.h"
  43 #include "convolution_kernel_mmad_slm_7x7_rep4.h"
  44 #include "convolution_kernel_byxf_fs_bs_yx_bsv4_fsv32.h"
  45 #include "convolution_kernel_mmad_batched_block.h"
  46 #include "convolution_kernel_mmad_batched_block_1x1.h"
  47 #include "convolution_kernel_mmad_32x32sg_128x128wg_slm_int8.h"
  48 #include "convolution_kernel_mmad_32x32sg_224x128wg_slm_int8.h"
  49 #include "convolution_kernel_mmad_32x32sg_slm_int8.h"
  50 #include "convolution_kernel_byx8_f4__fs_bs_yx_bsv4_fsv32.h"
  51 #include "convolution_kernel_imad_3x3.h"
  52 #include "convolution_kernel_imad_1x1.h"
  53 #include "convolution_kernel_imad_7x7.h"
  54
  55 namespace kernel_selector
  56 {
  57     convolution_kernel_selector::convolution_kernel_selector()
  58     {
  59         Attach<ConvolutionKernel_bfyx_Ref>();
  60         Attach<convolution_kernel_bfyx_1x1_opt>();
  61         Attach<ConvolutionKernel_bfyx_GEMMLike>();
  62         Attach<ConvolutionKernel_bfyx_Direct_10_10_12>();
  63         Attach<ConvolutionKernel_bfyx_os_iyx_osv16>();
  64         // commented out to not get in our way, will enable in future after autotuning
  65 //        Attach<ConvolutionKernel_bfyx_os_iyx_osv16_2_sg>();
  66         Attach<ConvolutionKernel_yxfb_Ref>();
  67         Attach<ConvolutionKernel_yxfb_yxio_b16>();
  68         Attach<ConvolutionKernel_yxfb_yxio_b8>();
  69         //Attach<ConvolutionKernel_yxfb_yxio_b1_block>(); // TODO: need to finish integration
  70         Attach<ConvolutionKernel_yxfb_yxio_b1_block_mulitple_x>();
  71         //Attach<ConvolutionKernel_bfyx_3x3_dw_opt>();
  72         Attach<ConvolutionKernel_Winograd_2x3_s1>();
  73         Attach<ConvolutionKernel_Winograd_2x3_s1_fused>();
  74         Attach<ConvolutionKernel_Winograd_6x3_s1_fused>();
  75         Attach<ConvolutionKernel_bfyx_1x1>();
  76         Attach<ConvolutionKernel_bfyx_1x1_gemm_buf>();
  77         Attach<ConvolutionKernel_MMAD>();
  78         Attach<ConvolutionKernel_MMAD_blocks>();
  79         Attach<ConvolutionKernel_1x1_gemm_MMAD>();
  80         Attach<ConvolutionKernel_byxf_af32_depthiwise>();
  81         Attach<ConvolutionKernel_mmad_batched>();
  82         Attach<ConvolutionKernel_bfyx_depthwise_weights_lwg>();
  83         Attach<ConvolutionKernel_mmad_slm_2x14_rep4>();
  84         Attach<ConvolutionKernel_mmad_slm_7x7_rep4>();
  85         Attach<ConvolutionKernel_mmad_32x32sg_128x128wg_slm_int8>();
  86         Attach<ConvolutionKernel_mmad_32x32sg_224x128wg_slm_int8>();
  87         Attach<ConvolutionKernel_byxf_fs_bs_yx_bsv4_fsv32>();
  88         Attach<ConvolutionKernel_byx8_f4__fs_bs_yx_bsv4_fsv32>();
  89         Attach<ConvolutionKernel_mmad_batched_block>();
  90         Attach<ConvolutionKernel_mmad_batched_block_1x1>();
  91 //        Attach<ConvolutionKernel_mmad_32x32sg_slm_int8>();
  92         //Attach<ConvolutionKernel_Tutorial>(); //In order to use this implementation for tutorial purposes please uncomment this line
  93         Attach<ConvolutionKernel_imad_3x3>();
  94         Attach<ConvolutionKernel_imad_1x1>();
  95         Attach<ConvolutionKernel_imad_7x7>();
  96     }
  97
  98     KernelsData convolution_kernel_selector::GetBestKernels(const Params& params, const optional_params& options) const
  99     {
 100         return GetAutoTuneBestKernel(params, options, KernelType::CONVOLUTION);
 101     }
 102 }