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99 lines
3.2 KiB
99 lines
3.2 KiB
// Copyright (c) 2018 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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#include <map>
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#include <unordered_map>
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#include <vector>
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#include "paddle/fluid/framework/op_kernel_type.h"
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#include "paddle/fluid/framework/tensor.h"
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#include "paddle/fluid/framework/variable.h"
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namespace paddle {
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namespace framework {
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class OpKernelType;
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class Tensor;
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} // namespace framework
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} // namespace paddle
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#ifdef PADDLE_WITH_MKLDNN
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#include "paddle/fluid/platform/mkldnn_helper.h"
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#endif
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namespace paddle {
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namespace framework {
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#ifdef PADDLE_WITH_MKLDNN
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using MKLDNNDataType = mkldnn::memory::data_type;
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inline MKLDNNMemoryFormat ToMKLDNNFormat(const DataLayout& layout) {
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switch (layout) {
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case DataLayout::kNHWC:
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return MKLDNNMemoryFormat::nhwc;
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case DataLayout::kNCHW:
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return MKLDNNMemoryFormat::nchw;
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default:
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PADDLE_THROW(platform::errors::InvalidArgument(
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"Fail to convert layout %s to MKLDNN format.",
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DataLayoutToString(layout)));
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}
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}
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inline DataLayout ToPaddleLayout(const MKLDNNMemoryFormat& format) {
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switch (format) {
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case MKLDNNMemoryFormat::nhwc:
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return DataLayout::kNHWC;
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case MKLDNNMemoryFormat::nchw:
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return DataLayout::kNCHW;
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default:
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PADDLE_THROW(platform::errors::InvalidArgument(
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"Fail to convert MKLDNN format to paddle layout."));
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}
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}
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inline MKLDNNDataType ToMKLDNNDataType(proto::VarType::Type type) {
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static std::unordered_map<int, MKLDNNDataType> dict{
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{DataTypeTrait<float>::DataType(), MKLDNNDataType::f32},
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{DataTypeTrait<int8_t>::DataType(), MKLDNNDataType::s8},
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{DataTypeTrait<uint8_t>::DataType(), MKLDNNDataType::u8},
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{DataTypeTrait<int32_t>::DataType(), MKLDNNDataType::s32},
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{DataTypeTrait<platform::bfloat16>::DataType(), MKLDNNDataType::bf16}};
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auto iter = dict.find(static_cast<int>(type));
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if (iter != dict.end()) return iter->second;
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return MKLDNNDataType::undef;
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}
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void innerTransDataLayoutFromMKLDNN(DataLayout in_layout, DataLayout out_layout,
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const Tensor& in, Tensor* out,
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platform::Place place);
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void TransDataLayoutFromMKLDNN(const OpKernelType& kernel_type_for_var,
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const OpKernelType& expected_kernel_type,
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const Tensor& in, Tensor* out);
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void* GetDataFromTensor(const Tensor& tensor, MKLDNNDataType type);
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#endif
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std::vector<int> GetAxis(const DataLayout& from, const DataLayout& to);
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void TransDataLayout(const OpKernelType& kernel_type_for_var,
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const OpKernelType& expected_kernel_type, const Tensor& in,
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Tensor* out);
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} // namespace framework
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} // namespace paddle
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