73 lines
2.3 KiB
C++
73 lines
2.3 KiB
C++
/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include "paddle/common/ddim.h"
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#include "paddle/common/layout.h"
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namespace phi {
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namespace funcs {
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#define CUDNN_PER_ACTIVATION_THRESHOLD 10240
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#define CUDNN_SPATIAL_THRESHOLD_TRAIN 880801
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#define CUDNN_SPATIAL_THRESHOLD_EVAL 65535
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inline void ExtractNCWHD(const DDim &dims,
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const DataLayout &data_layout,
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int *N,
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int *C,
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int *H,
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int *W,
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int *D) {
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*N = dims[0];
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if (dims.size() == 2) {
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*C = dims[1];
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*H = 1;
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*W = 1;
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*D = 1;
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} else {
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*C = data_layout == DataLayout::NCHW ? dims[1] : dims[dims.size() - 1];
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*H = data_layout == DataLayout::NCHW ? dims[2] : dims[1];
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*W = dims.size() > 3 ? (data_layout == DataLayout::NCHW ? dims[3] : dims[2])
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: 1;
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*D = dims.size() > 4 ? (data_layout == DataLayout::NCHW ? dims[4] : dims[3])
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: 1;
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}
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}
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inline void ExtractNCWHD(const DDim &dims,
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const DataLayout &data_layout,
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int64_t *N,
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int64_t *C,
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int64_t *H,
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int64_t *W,
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int64_t *D) {
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*N = dims[0];
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if (dims.size() == 2) {
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*C = dims[1];
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*H = 1;
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*W = 1;
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*D = 1;
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} else {
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*C = data_layout == DataLayout::NCHW ? dims[1] : dims[dims.size() - 1];
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*H = data_layout == DataLayout::NCHW ? dims[2] : dims[1];
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*W = dims.size() > 3 ? (data_layout == DataLayout::NCHW ? dims[3] : dims[2])
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: 1;
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*D = dims.size() > 4 ? (data_layout == DataLayout::NCHW ? dims[4] : dims[3])
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: 1;
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}
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}
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} // namespace funcs
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} // namespace phi
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