inference-engine/thirdparty/clDNN/kernel_selector/core/actual_kernels/fully_connected/fully_connected_kernel_mmad_batched.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 "fully_connected_kernel_mmad_batched.h"
  18
  19 namespace kernel_selector
  20 {
  21     ParamsKey FullyConnected_mmad_batched::GetSupportedKey() const
  22     {
  23         ParamsKey k;
  24         k.EnableInputDataType(Datatype::INT8);
  25         k.EnableOutputDataType(Datatype::INT8);
  26         k.EnableInputWeightsType(WeightsType::INT8);
  27         k.EnableInputLayout(DataLayout::fs_bs_yx_bsv4_fsv32);
  28         k.EnableOutputLayout(DataLayout::fs_bs_yx_bsv4_fsv32);
  29         k.EnableOutputLayout(DataLayout::bf);
  30         k.EnableBiasPerOutput();
  31         k.EnableBiasPerFeature();
  32         k.EnableNonBiasTerm();
  33         k.EnableTensorOffset();
  34         k.EnableTensorPitches();
  35         k.EnableBatching();
  36         k.EnableInt8Quantization();
  37         k.EnableOutputCalibration();
  38         return k;
  39     }
  40
  41     bool FullyConnected_mmad_batched::Validate(const Params& p, const optional_params& o) const
  42     {
  43         if (!FullyConnectedKernelBase::Validate(p, o))
  44         {
  45             return false;
  46         }
  47
  48         const auto& params = static_cast<const fully_connected_params&>(p);
  49
  50         // we do not support padded input
  51         if (params.inputs[0].X().pad.Total() != 0 || params.inputs[0].Y().pad.Total() != 0)
  52             return false;
  53
  54         size_t batch = params.inputs[0].Batch().v;
  55         // batch must be a multiple of 8
  56         if (batch % 8 != 0)
  57         {
  58             return false;
  59         }
  60
  61         return true;
  62     }
  63
  64     JitConstants FullyConnected_mmad_batched::GetJitConstants(const fully_connected_params& params, const DispatchData& runInfo) const
  65     {
  66         auto jit = Parent::GetJitConstants(params, runInfo);
  67
  68         jit.AddConstant(MakeJitConstant("SUB_GROUP_SIZE", runInfo.lws1));
  69
  70         // pitch for special block format used in this kernel
  71         const size_t ifm_32_aligned = Align(params.weights.IFM().v, 32);
  72         const size_t filter_ofm_block_pitch = (ifm_32_aligned / 32) * params.weights.X().v * params.weights.Y().v * 4 * 8 * 8;
  73         jit.AddConstant(MakeJitConstant("FILTER_OFM_BLOCK_PITCH", filter_ofm_block_pitch));
  74
  75         const size_t in_x_pitch = 32 * 4;
  76         const size_t in_y_pitch = 32 * 4 * params.inputs[0].X().LogicalDimPadded();
  77         const size_t in_b_block_pitch = in_y_pitch * params.inputs[0].Y().LogicalDimPadded();
  78         const size_t in_f_block_pitch = in_b_block_pitch * ((params.inputs[0].Batch().v + 3) / 4);
  79         const size_t in_offset = in_x_pitch * params.inputs[0].X().pad.before + in_y_pitch * params.inputs[0].Y().pad.before;
  80
  81         jit.AddConstant(MakeJitConstant("IN_X_PITCH", in_x_pitch));
  82         jit.AddConstant(MakeJitConstant("IN_Y_PITCH", in_y_pitch));
  83         jit.AddConstant(MakeJitConstant("IN_B_BLOCK_PITCH", in_b_block_pitch));
  84         jit.AddConstant(MakeJitConstant("IN_F_BLOCK_PITCH", in_f_block_pitch));
  85         jit.AddConstant(MakeJitConstant("IN_OFFSET", in_offset));
  86
  87         return jit;
  88     }
  89
  90     FullyConnected_mmad_batched::DispatchData FullyConnected_mmad_batched::SetDefault(const fully_connected_params& params, int) const
  91     {
  92         auto runInfo = Parent::SetDefault(params);
  93
  94         constexpr size_t sub_group_size = 8;
  95
  96         const auto of_maps = params.output.Feature().v;
  97         const size_t of_threads_per_batch = RoundUp(of_maps, sub_group_size);
  98
  99         runInfo.gws0 = params.output.Batch().v / 8; // we process 8 batches in a single WG
 100         runInfo.gws1 = of_threads_per_batch;
 101         runInfo.gws2 = 1;
 102
 103         runInfo.lws0 = 1;
 104         runInfo.lws1 = sub_group_size;
 105         runInfo.lws2 = 1;
 106
 107         runInfo.effiency = FORCE_PRIORITY_1;
 108         return runInfo;
 109     }
 110
 111     KernelsData FullyConnected_mmad_batched::GetKernelsData(const Params& params, const optional_params& options) const
 112     {
 113         KernelsData res = {};
 114         for (size_t i = 0; i < autoTuneOptions.size(); i++)
 115         {
 116             KernelsData kd = GetTunedKernelsDataByIndex(params, options, DataLayout::fs_bs_yx_bsv4_fsv32,
 117                 { WeightsLayout::os_is_yx_isa8_osv8_isv4 }, FORCE_PRIORITY_1, (int)i);
 118             if (!kd.empty())
 119             {
 120                 res.emplace_back(kd[0]);
 121             }
 122         }
 123         return res;
 124     }
 125 }