[MKL-DNN] Tensor modifications revert (#16462)
* Revert "[MKL-DNN] Fix to crash of Transformer when mkldnn is to be used (#16233)" This reverts commitrevert-16555-model_data_cryption_link_all_lib13816dd4ac. Apart from enabling transformer for MKL-DNN * Revert "- MKL-DNN pooling updated to set_prim_desc" This reverts commitc63f6b2039. Conflicts: paddle/fluid/operators/mkldnn/concat_mkldnn_op.cc * Revert "[MKL-DNN] MKL-DNN specific Tensor modification (#15429)" test=develop This reverts commitdec9cf53c8. * - concat compilation fix - lint test=develop - Lint fixes test=develop - Lint fixes test=develop - Fix Transpose MKLDNN op test=develop
Jacek Czaja
6 years ago
committed by
tensor-tang
parent
4143a1c216
commit
2632327429
@ -1,69 +0,0 @@
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/* Copyright (c) 2019 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 <mkldnn.h>
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#include <string>
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namespace paddle {
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namespace platform {
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inline mkldnn::memory::primitive_desc create_prim_desc_from_dims(
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const std::vector<int>& ltz, mkldnn::memory::format fmt,
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mkldnn::memory::data_type data_type = mkldnn::memory::data_type::f32) {
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mkldnn_memory_desc_t mem_fmt;
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mem_fmt.primitive_kind = mkldnn_memory;
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mem_fmt.ndims = ltz.size();
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for (unsigned int i = 0; i < ltz.size(); ++i) {
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mem_fmt.dims[i] = ltz[i]; // logical dimensions (nchw format,
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// regardless physical layout)
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}
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mem_fmt.data_type = static_cast<mkldnn_data_type_t>(data_type);
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mem_fmt.format = static_cast<mkldnn_memory_format_t>(fmt);
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unsigned int total_stride = 1;
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for (int i = ltz.size() - 1; i >= 0; --i) {
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mem_fmt.layout_desc.blocking.padding_dims[i] =
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ltz[i]; // logical dimensions (nchw format, regardless physical
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// layout)
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mem_fmt.layout_desc.blocking.block_dims[i] = 1;
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mem_fmt.layout_desc.blocking.offset_padding_to_data[i] = 0; // no offset
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mem_fmt.layout_desc.blocking.strides[0][i] = total_stride;
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mem_fmt.layout_desc.blocking.strides[1][i] = 1;
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total_stride *= ltz[i];
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}
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mem_fmt.layout_desc.blocking.offset_padding = 0; // no initial offset
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auto& pool = platform::DeviceContextPool::Instance();
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auto place = paddle::platform::CPUPlace();
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auto* dev_ctx = dynamic_cast<platform::MKLDNNDeviceContext*>(pool.Get(place));
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auto& cpu_engine = dev_ctx->GetEngine();
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return mkldnn::memory::primitive_desc(mem_fmt, cpu_engine);
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}
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inline mkldnn::memory::primitive_desc create_prim_desc_from_format(
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const std::vector<int>& ltz, const mkldnn::memory::format format,
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const mkldnn::memory::data_type data_type) {
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auto md = mkldnn::memory::desc({ltz}, data_type, format);
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auto& pool = platform::DeviceContextPool::Instance();
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auto place = paddle::platform::CPUPlace();
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auto dev_ctx = dynamic_cast<platform::MKLDNNDeviceContext*>(pool.Get(place));
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PADDLE_ENFORCE_NOT_NULL(dev_ctx, "Could not get valid device");
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auto& cpu_engine = dev_ctx->GetEngine();
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return mkldnn::memory::primitive_desc(md, cpu_engine);
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}
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} // namespace platform
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} // namespace paddle
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