96 lines
3.2 KiB
C++
96 lines
3.2 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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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#ifdef PADDLE_WITH_DNNL
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#include "dnnl.hpp" // NOLINT
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#endif
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#include "paddle/common/layout.h"
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#include "paddle/phi/common/data_type.h"
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#include "paddle/phi/common/place.h"
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#include "paddle/phi/core/dense_tensor.h"
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namespace phi {
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namespace funcs {
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#ifdef PADDLE_WITH_DNNL
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using OneDNNDataType = dnnl::memory::data_type;
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using OneDNNMemoryFormat = dnnl::memory::format_tag;
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inline OneDNNMemoryFormat ToOneDNNFormat(const DataLayout& layout) {
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switch (layout) {
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case DataLayout::NHWC:
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return OneDNNMemoryFormat::nhwc;
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case DataLayout::NCHW:
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return OneDNNMemoryFormat::nchw;
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case DataLayout::NCDHW:
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return OneDNNMemoryFormat::ncdhw;
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case DataLayout::NDHWC:
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return OneDNNMemoryFormat::ndhwc;
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default:
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PADDLE_THROW(
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errors::InvalidArgument("Fail to convert layout %s to oneDNN format.",
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DataLayoutToString(layout)));
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}
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}
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inline OneDNNDataType ToOneDNNDataType(DataType type) {
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#if __GNUC__ > 5
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using DataTypeMapping = std::unordered_map<DataType, OneDNNDataType>;
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#else
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struct DataTypeHash {
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std::size_t operator()(const DataType& f) const {
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return std::hash<int>{}(static_cast<int>(f));
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}
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};
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struct DataTypeEqual {
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bool operator()(const DataType& lhs, const DataType& rhs) const {
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return static_cast<int>(lhs) == static_cast<int>(rhs);
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}
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};
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using DataTypeMapping =
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std::unordered_map<DataType, OneDNNDataType, DataTypeHash, DataTypeEqual>;
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#endif
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static DataTypeMapping dict{{DataType::FLOAT32, OneDNNDataType::f32},
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{DataType::INT8, OneDNNDataType::s8},
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{DataType::UINT8, OneDNNDataType::u8},
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{DataType::INT32, OneDNNDataType::s32},
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{DataType::BFLOAT16, OneDNNDataType::bf16}};
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auto iter = dict.find(type);
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if (iter != dict.end()) return iter->second;
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return OneDNNDataType::undef;
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}
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PADDLE_API void TransDataLayoutFromOneDNN(DataLayout in_layout,
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DataLayout out_layout,
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const DenseTensor& in,
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DenseTensor* out,
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Place place,
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bool always_copy = false);
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TEST_API void* GetDataFromTensor(const DenseTensor& tensor,
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OneDNNDataType type);
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PADDLE_API dnnl::memory::desc make_memory_desc(const DenseTensor& ref_tensor,
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DataLayout target_layout);
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#endif
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} // namespace funcs
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} // namespace phi
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