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体验新版 GitCode,发现更多精彩内容 >>
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dfbd1cc3
编写于
9月 11, 2018
作者:
J
Jacek Czaja
提交者:
GitHub
9月 11, 2018
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差异文件
Merge pull request #13209 from Sand3r-/mgallus/conv-relu-fuse
[MKLDNN] Fuse Conv+BatchNorm + ReLU
上级
2ed7982d
5d34ef61
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
75 addition
and
12 deletion
+75
-12
paddle/fluid/operators/conv_mkldnn_op.cc
paddle/fluid/operators/conv_mkldnn_op.cc
+37
-9
paddle/fluid/operators/conv_op.cc
paddle/fluid/operators/conv_op.cc
+2
-0
python/paddle/fluid/transpiler/inference_transpiler.py
python/paddle/fluid/transpiler/inference_transpiler.py
+36
-3
未找到文件。
paddle/fluid/operators/conv_mkldnn_op.cc
浏览文件 @
dfbd1cc3
...
...
@@ -299,6 +299,7 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
std
::
vector
<
int
>
strides
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"strides"
);
std
::
vector
<
int
>
paddings
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
std
::
vector
<
int
>
dilations
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"dilations"
);
bool
fuse_relu
=
ctx
.
Attr
<
bool
>
(
"fuse_relu"
);
int
groups
=
ctx
.
Attr
<
int
>
(
"groups"
);
// TODO(pzelazko-intel) add support for group convolution and dilation
...
...
@@ -351,11 +352,12 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
bias_tz
=
paddle
::
framework
::
vectorize2int
(
bias
->
dims
());
auto
bias_md
=
platform
::
MKLDNNMemDesc
(
bias_tz
,
platform
::
MKLDNNGetDataType
<
T
>
(),
memory
::
format
::
x
);
conv_pd
=
ConvFwdPrimitiveDesc
(
src_md
,
weights_md
,
bias_md
,
dst_md
,
strides
,
paddings
,
mkldnn_engine
);
conv_pd
=
ConvFwdPrimitiveDesc
(
src_md
,
weights_md
,
bias_md
,
dst_md
,
strides
,
paddings
,
mkldnn_engine
,
fuse_relu
);
}
else
{
conv_pd
=
ConvFwdPrimitiveDesc
(
src_md
,
weights_md
,
dst_md
,
strides
,
paddings
,
mkldnn_engine
);
paddings
,
mkldnn_engine
,
fuse_relu
);
}
// Save conv_pd/src_memory/weights_memory for backward pass
dev_ctx
.
SetBlob
(
key_conv_pd
,
conv_pd
);
...
...
@@ -405,11 +407,26 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
}
private:
mkldnn
::
primitive_attr
AddRelu
()
const
{
// Fusion with ReLU layer is executed through the PostOps feature. Create a
// PostOps object and configure it to execute an eltwise relu operation.
mkldnn
::
primitive_attr
conv_attr
;
constexpr
float
scale
=
1.0
f
;
constexpr
float
negative_slope
=
0.0
f
;
constexpr
float
placeholder
=
0.0
f
;
mkldnn
::
post_ops
post_operations
;
post_operations
.
append_eltwise
(
scale
,
mkldnn
::
algorithm
::
eltwise_relu
,
negative_slope
,
placeholder
);
conv_attr
.
set_post_ops
(
post_operations
);
return
conv_attr
;
}
std
::
unique_ptr
<
mkldnn
::
convolution_forward
::
primitive_desc
>
ConvFwdPrimitiveDesc
(
const
memory
::
desc
&
src
,
const
memory
::
desc
&
weights
,
const
memory
::
desc
&
dst
,
const
std
::
vector
<
int
>&
strides
,
const
std
::
vector
<
int
>&
paddings
,
const
mkldnn
::
engine
&
engine
)
const
{
const
mkldnn
::
engine
&
engine
,
const
bool
fuse_relu
)
const
{
memory
::
dims
stride_dims
=
{
strides
[
0
],
strides
[
1
]};
memory
::
dims
padding_dims
=
{
paddings
[
0
],
paddings
[
1
]};
...
...
@@ -418,8 +435,13 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
dst
,
stride_dims
,
padding_dims
,
padding_dims
,
mkldnn
::
padding_kind
::
zero
);
auto
p_conv_pd
=
new
mkldnn
::
convolution_forward
::
primitive_desc
(
conv_desc
,
engine
);
mkldnn
::
primitive_attr
conv_attr
;
if
(
fuse_relu
)
{
conv_attr
=
AddRelu
();
}
auto
p_conv_pd
=
new
mkldnn
::
convolution_forward
::
primitive_desc
(
conv_desc
,
conv_attr
,
engine
);
return
std
::
unique_ptr
<
mkldnn
::
convolution_forward
::
primitive_desc
>
(
p_conv_pd
);
...
...
@@ -430,7 +452,8 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
const
memory
::
desc
&
bias
,
const
memory
::
desc
&
dst
,
const
std
::
vector
<
int
>&
strides
,
const
std
::
vector
<
int
>&
paddings
,
const
mkldnn
::
engine
&
engine
)
const
{
const
mkldnn
::
engine
&
engine
,
const
bool
fuse_relu
)
const
{
memory
::
dims
stride_dims
=
{
strides
[
0
],
strides
[
1
]};
memory
::
dims
padding_dims
=
{
paddings
[
0
],
paddings
[
1
]};
...
...
@@ -439,8 +462,13 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
bias
,
dst
,
stride_dims
,
padding_dims
,
padding_dims
,
mkldnn
::
padding_kind
::
zero
);
auto
p_conv_pd
=
new
mkldnn
::
convolution_forward
::
primitive_desc
(
conv_desc
,
engine
);
mkldnn
::
primitive_attr
conv_attr
;
if
(
fuse_relu
)
{
conv_attr
=
AddRelu
();
}
auto
p_conv_pd
=
new
mkldnn
::
convolution_forward
::
primitive_desc
(
conv_desc
,
conv_attr
,
engine
);
return
std
::
unique_ptr
<
mkldnn
::
convolution_forward
::
primitive_desc
>
(
p_conv_pd
);
...
...
paddle/fluid/operators/conv_op.cc
浏览文件 @
dfbd1cc3
...
...
@@ -162,6 +162,8 @@ void Conv2DOpMaker::Make() {
AddAttr
<
bool
>
(
"use_mkldnn"
,
"(bool, default false) Only used in mkldnn kernel"
)
.
SetDefault
(
false
);
AddAttr
<
bool
>
(
"fuse_relu"
,
"(bool, default false) Only used in mkldnn kernel"
)
.
SetDefault
(
false
);
AddAttr
<
std
::
string
>
(
"data_format"
,
"(string, default NCHW) Only used in "
...
...
python/paddle/fluid/transpiler/inference_transpiler.py
浏览文件 @
dfbd1cc3
...
...
@@ -60,12 +60,46 @@ class InferenceTranspiler(object):
if
not
isinstance
(
scope
,
core
.
Scope
):
raise
TypeError
(
"scope should be as Scope type or None"
)
use_mkldnn
=
bool
(
os
.
getenv
(
"FLAGS_use_mkldnn"
,
False
))
self
.
_fuse_batch_norm
(
program
,
place
,
scope
)
if
use_mkldnn
:
self
.
_fuse_relu_mkldnn
(
program
)
self
.
_fuse_conv_bias_mkldnn
(
program
)
self
.
_fuse_conv_relu_mkldnn
(
program
)
self
.
_fuse_bn_relu_mkldnn
(
program
)
def
_fuse_conv_relu_mkldnn
(
self
,
program
):
'''
Transpile the program by fused relu activation for MKLDNN program.
Relu activation following convolution OP can be fused by adding
'fuse_relu' attribute to convolution OP.
The result of fuse is:
- before:
- conv->relu->any_other_op
- after:
- conv->any_other_op
:param program: program to transpile
:type program: Program
'''
self
.
block
=
program
.
block
(
0
)
i
=
0
while
i
<
len
(
self
.
block
.
ops
):
current_op
=
self
.
block
.
ops
[
i
]
if
current_op
.
type
in
[
'conv2d'
]:
next_op
=
self
.
block
.
ops
[
i
+
1
]
if
next_op
.
type
==
'relu'
:
# modify conv OP to include relu
current_op
.
set_attr
(
"fuse_relu"
,
True
)
# remove conv OP
self
.
block
.
_remove_op
(
i
+
1
)
i
=
i
+
1
# TODO(luotao): use clone() method to flush the program.desc in force,
# since some large program.desc will not be flushed immediately.
# And a better solution will be considered later.
program
=
program
.
clone
()
def
_fuse_relu_mkldnn
(
self
,
program
):
def
_fuse_
bn_
relu_mkldnn
(
self
,
program
):
'''
Transpile the program by fused relu activation for MKLDNN program.
...
...
@@ -159,7 +193,6 @@ class InferenceTranspiler(object):
self
.
_fuse_conv_bias
(
i
,
current_op
,
next_op
)
self
.
block
.
_remove_op
(
i
+
1
)
# Remove old conv
self
.
block
.
_remove_op
(
i
+
1
)
# Remove elementwise_add
i
=
i
+
1
i
=
i
+
1
self
.
_remove_unused_var
()
...
...
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