wehub-resource-sync
67 lines
1.7 KiB
C++
67 lines
1.7 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 <string>
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#include "paddle/phi/backends/gpu/gpu_dnn.h"
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namespace phi {
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using PoolingMode = phi::backends::gpu::PoolingMode;
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using ScopedPoolingDescriptor = phi::backends::gpu::ScopedPoolingDescriptor;
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using ScopedTensorDescriptor = phi::backends::gpu::ScopedTensorDescriptor;
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template <typename T>
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using ScalingParamType =
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typename phi::backends::gpu::CudnnDataType<T>::ScalingParamType;
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template <typename T>
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class CudnnIndexType;
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template <>
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class CudnnIndexType<int> {
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public:
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#ifdef PADDLE_WITH_CUDA
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static const dnnDataType_t type = CUDNN_DATA_INT32;
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#else
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static const dnnDataType_t type = miopenInt32;
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#endif
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};
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template <>
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class CudnnIndexType<int8_t> {
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public:
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#ifdef PADDLE_WITH_CUDA
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static const dnnDataType_t type = CUDNN_DATA_INT8;
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#else
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static const dnnDataType_t type = miopenInt8;
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#endif
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};
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inline DataLayout GetLayoutFromStr(std::string data_format) {
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if (data_format == "NHWC") {
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return DataLayout::NHWC;
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} else if (data_format == "NCHW") {
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return DataLayout::NCHW;
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} else if (data_format == "NCDHW") {
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return DataLayout::NCDHW;
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} else {
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return DataLayout::NCDHW;
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}
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}
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} // namespace phi
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