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90 lines
3.4 KiB
C++
90 lines
3.4 KiB
C++
/*******************************************************************************
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*
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* MIT License
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*
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* Copyright (c) 2023 Advanced Micro Devices, Inc.
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*
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*******************************************************************************/
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#ifndef MLO_GROUPNORMHOST_H_
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#define MLO_GROUPNORMHOST_H_
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#include <miopen/tensor.hpp>
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////////////////////////////////////////////////////////////
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//
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///////////////////////////////////////////////////////////
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template <typename Tgpu, typename Tcheck>
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int32_t mloGroupNormForwardRunHost(miopenTensorDescriptor_t inputDesc,
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Tgpu* input,
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Tgpu* weight,
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Tgpu* bias,
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Tcheck* outputhost,
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Tcheck* meanhost,
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Tcheck* rstdhost,
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uint64_t num_groups,
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float eps,
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miopenNormMode_t mode,
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bool use_multithread)
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{
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auto dims = miopen::deref(inputDesc).GetLengths();
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size_t numel = miopen::deref(inputDesc).GetElementSize();
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size_t numel_per_channel = numel / dims[0] / dims[1];
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size_t num_channels = dims[1];
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size_t outer_size = dims[0] * num_groups;
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size_t inner_size = numel / outer_size;
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size_t min_grain = use_multithread ? 8 : outer_size;
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miopen::par_for(outer_size, min_grain, [&](size_t o) {
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Tcheck pmean = 0.0f;
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Tcheck pvar = 0.0f;
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for(size_t i = 0; i < inner_size; i++)
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{
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Tcheck tmp = static_cast<Tcheck>(input[o * inner_size + i]);
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pmean += tmp;
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pvar += tmp * tmp;
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}
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pmean = pmean / inner_size;
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pvar = pvar / inner_size - pmean * pmean;
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Tcheck prstd = 1.0f / sqrt(pvar + eps);
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meanhost[o] = pmean;
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rstdhost[o] = prstd;
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for(size_t i = 0; i < inner_size; i++)
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{
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size_t idx = o * inner_size + i;
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size_t c = (idx / numel_per_channel) % num_channels;
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Tcheck pweight = mode ? static_cast<Tcheck>(weight[c]) : 1;
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Tcheck pbias = mode ? static_cast<Tcheck>(bias[c]) : 0;
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outputhost[idx] = (static_cast<Tcheck>(input[idx]) - pmean) * prstd * pweight + pbias;
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}
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});
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return 0;
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}
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#endif
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