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79 lines
2.9 KiB
C++
79 lines
2.9 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 GUARD_CPU_GROUPNORM_HPP
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#define GUARD_CPU_GROUPNORM_HPP
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#include "tensor_holder.hpp"
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template <class T>
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void cpu_groupnorm_forward(tensor<T> input,
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tensor<T> weight,
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tensor<T> bias,
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tensor<T>& ref_output,
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tensor<T>& ref_mean,
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tensor<T>& ref_rstd,
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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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{
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auto dims = input.desc.GetLengths();
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size_t numel = input.desc.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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miopen::par_ford(outer_size)([&](int32_t o) {
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T mean_v = 0.0f;
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T var_v = 0.0f;
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miopen::ford(inner_size)([&](int32_t i) {
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T tmp = input[o * inner_size + i];
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mean_v += tmp;
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var_v += tmp * tmp;
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});
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mean_v = mean_v / inner_size;
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var_v = var_v / inner_size - mean_v * mean_v;
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T rstd_v = 1.0f / sqrt(var_v + eps);
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ref_mean[o] = mean_v;
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ref_rstd[o] = rstd_v;
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miopen::ford(inner_size)([&](int32_t i) {
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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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T weight_v = mode ? weight[c] : 1;
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T bias_v = mode ? bias[c] : 0;
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ref_output[idx] = (input[idx] - mean_v) * rstd_v * weight_v + bias_v;
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});
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});
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}
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#endif
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