[MKL-DNN ]Added transpose/transpose2 Op (#14872)
* - Added transpose MKLDNN Op - Few basic UT works - Added 1D transpose - implementing generic mem desc for MKLDNN transpose - Modified trnaspose op to support more dimensional data eg. 5,6..10 - Added is_test attribute to transpose op test=develop * - Added support for MKLDNN::memory::format::any for Transpose MKLDNN op test=develop * - Additional transpose mkldnn op correction to mkldnn layout test=develop * Cosmetic fixes test=develop * - Removed const_cast to obey coding standard test=developfor_weibo
Jacek Czaja
6 years ago
committed by
Tao Luo
parent
6c66b3d496
commit
aa6e9c30be
@ -0,0 +1,124 @@
|
||||
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License. */
|
||||
|
||||
#include "paddle/fluid/framework/data_layout_transform.h"
|
||||
#include "paddle/fluid/framework/op_registry.h"
|
||||
#include "paddle/fluid/memory/malloc.h"
|
||||
#include "paddle/fluid/platform/mkldnn_reuse.h"
|
||||
|
||||
namespace paddle {
|
||||
namespace operators {
|
||||
|
||||
using Tensor = framework::Tensor;
|
||||
using framework::DataLayout;
|
||||
|
||||
template <typename T>
|
||||
class TransposeMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
|
||||
public:
|
||||
void Compute(const paddle::framework::ExecutionContext& ctx) const override {
|
||||
PADDLE_ENFORCE(paddle::platform::is_cpu_place(ctx.GetPlace()),
|
||||
"It must use CPUPlace.");
|
||||
const bool is_test = ctx.Attr<bool>("is_test");
|
||||
PADDLE_ENFORCE(
|
||||
is_test == true,
|
||||
"ConvTransposeMKLDNN works only for inference!. Set is_test = True");
|
||||
auto& dev_ctx =
|
||||
ctx.template device_context<paddle::platform::MKLDNNDeviceContext>();
|
||||
const auto& mkldnn_engine = dev_ctx.GetEngine();
|
||||
std::vector<int> axis = ctx.Attr<std::vector<int>>("axis");
|
||||
int ndims = axis.size();
|
||||
auto* input = ctx.Input<Tensor>("X");
|
||||
auto* output = ctx.Output<Tensor>("Out");
|
||||
const T* input_data = input->data<T>();
|
||||
|
||||
if (ndims == 1) {
|
||||
output->ShareDataWith(*input);
|
||||
return;
|
||||
}
|
||||
|
||||
std::vector<int> nchw_axis(ndims, 0);
|
||||
for (size_t i = 0; i < nchw_axis.size(); ++i) {
|
||||
nchw_axis[i] = i;
|
||||
}
|
||||
|
||||
std::vector<int> nchw_tz = paddle::framework::vectorize2int(input->dims());
|
||||
std::string data_format = ctx.Attr<std::string>("data_format");
|
||||
|
||||
auto src_md =
|
||||
input->format() != mkldnn::memory::format::nchw
|
||||
? platform::MKLDNNMemDesc(nchw_tz, platform::MKLDNNGetDataType<T>(),
|
||||
input->format())
|
||||
: Axis2MemoryDesc(nchw_tz, nchw_axis);
|
||||
|
||||
this->TransposeKernel(ctx.GetPlace(), Axis2MemoryDesc(nchw_tz, axis),
|
||||
src_md, output, input_data, nchw_tz, mkldnn_engine);
|
||||
}
|
||||
|
||||
protected:
|
||||
mkldnn::memory::desc Axis2MemoryDesc(std::vector<int>& nchw_tz,
|
||||
std::vector<int>& axis) const {
|
||||
mkldnn_memory_desc_t mem_fmt;
|
||||
|
||||
mem_fmt.primitive_kind = mkldnn_memory;
|
||||
mem_fmt.ndims = axis.size();
|
||||
for (unsigned int i = 0; i < nchw_tz.size(); ++i) {
|
||||
mem_fmt.dims[i] = nchw_tz[i]; // logical dimensions (nchw format,
|
||||
// regardless physical layout)
|
||||
}
|
||||
mem_fmt.data_type = mkldnn_f32;
|
||||
mem_fmt.format = mkldnn_blocked;
|
||||
|
||||
unsigned int total_stride = 1;
|
||||
for (int i = nchw_tz.size() - 1; i >= 0; --i) {
|
||||
mem_fmt.layout_desc.blocking.padding_dims[i] =
|
||||
nchw_tz[i]; // logical dimensions (nchw format, regardless physical
|
||||
// layout)
|
||||
mem_fmt.layout_desc.blocking.block_dims[i] = 1;
|
||||
mem_fmt.layout_desc.blocking.offset_padding_to_data[i] = 0; // no offset
|
||||
mem_fmt.layout_desc.blocking.strides[0][axis[i]] = total_stride;
|
||||
mem_fmt.layout_desc.blocking.strides[1][axis[i]] = 1;
|
||||
total_stride *= nchw_tz[axis[i]];
|
||||
}
|
||||
mem_fmt.layout_desc.blocking.offset_padding = 0; // no initial offset
|
||||
return mem_fmt;
|
||||
}
|
||||
|
||||
void TransposeKernel(platform::Place place, mkldnn::memory::desc md_o,
|
||||
mkldnn::memory::desc md_i, Tensor* output,
|
||||
const T* data_i, std::vector<int>& nchw_dims,
|
||||
const mkldnn::engine& eng) const {
|
||||
// Make Memory primitive descriptors
|
||||
auto mpd_o = mkldnn::memory::primitive_desc(md_o, eng);
|
||||
auto mpd_i = mkldnn::memory::primitive_desc(md_i, eng);
|
||||
|
||||
auto data_o = output->mutable_data<T>(
|
||||
place, paddle::memory::Allocator::kDefault, mpd_o.get_size());
|
||||
|
||||
auto src = mkldnn::memory(mpd_i, (T*)(data_i));
|
||||
auto dst = mkldnn::memory(mpd_o, data_o);
|
||||
|
||||
auto r = mkldnn::reorder(src, dst);
|
||||
mkldnn::stream(mkldnn::stream::kind::eager).submit({r}).wait();
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace operators
|
||||
} // namespace paddle
|
||||
|
||||
namespace ops = paddle::operators;
|
||||
|
||||
REGISTER_OP_KERNEL(transpose2, MKLDNN, ::paddle::platform::CPUPlace,
|
||||
ops::TransposeMKLDNNOpKernel<float>);
|
||||
REGISTER_OP_KERNEL(transpose, MKLDNN, ::paddle::platform::CPUPlace,
|
||||
ops::TransposeMKLDNNOpKernel<float>);
|
||||
@ -0,0 +1,76 @@
|
||||
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from __future__ import print_function
|
||||
|
||||
import unittest
|
||||
|
||||
from test_transpose_op import TestTransposeOp
|
||||
|
||||
|
||||
class TestTransposeMKLDNN(TestTransposeOp):
|
||||
def init_op_type(self):
|
||||
self.op_type = "transpose2"
|
||||
self.use_mkldnn = True
|
||||
self.is_test = True
|
||||
return
|
||||
|
||||
def test_check_grad(self):
|
||||
return
|
||||
|
||||
def test_check_grad_no_input(self):
|
||||
return
|
||||
|
||||
def test_check_grad_no_filter(self):
|
||||
return
|
||||
|
||||
|
||||
class TestCase0MKLDNN(TestTransposeMKLDNN):
|
||||
def initTestCase(self):
|
||||
self.shape = (3, )
|
||||
self.axis = (0, )
|
||||
|
||||
|
||||
class TestCase1a(TestTransposeMKLDNN):
|
||||
def initTestCase(self):
|
||||
self.shape = (3, 4, 5)
|
||||
self.axis = (0, 2, 1)
|
||||
|
||||
|
||||
class TestCase1b(TestTransposeMKLDNN):
|
||||
def initTestCase(self):
|
||||
self.shape = (3, 4, 5)
|
||||
self.axis = (2, 1, 0)
|
||||
|
||||
|
||||
class TestCase2(TestTransposeMKLDNN):
|
||||
def initTestCase(self):
|
||||
self.shape = (2, 3, 4, 5)
|
||||
self.axis = (0, 2, 3, 1)
|
||||
|
||||
|
||||
class TestCase3(TestTransposeMKLDNN):
|
||||
def initTestCase(self):
|
||||
self.shape = (2, 3, 4, 5, 6)
|
||||
self.axis = (4, 2, 3, 1, 0)
|
||||
|
||||
|
||||
class TestCase4(TestTransposeMKLDNN):
|
||||
def initTestCase(self):
|
||||
self.shape = (2, 3, 4, 5, 6, 1)
|
||||
self.axis = (4, 2, 3, 1, 0, 5)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
Loading…
Reference in new issue