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30d32035
编写于
5月 30, 2018
作者:
M
mozga-intel
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差异文件
Withdraw mkldnn mul
上级
654f5d3c
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
8 addition
and
308 deletion
+8
-308
paddle/fluid/operators/mul_mkldnn_op.cc
paddle/fluid/operators/mul_mkldnn_op.cc
+0
-197
paddle/fluid/operators/mul_op.cc
paddle/fluid/operators/mul_op.cc
+0
-39
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+5
-8
python/paddle/fluid/tests/unittests/test_mul_mkldnn_op.py
python/paddle/fluid/tests/unittests/test_mul_mkldnn_op.py
+0
-44
python/paddle/fluid/tests/unittests/test_mul_op.py
python/paddle/fluid/tests/unittests/test_mul_op.py
+2
-16
python/paddle/fluid/tests/unittests/test_operator_desc.py
python/paddle/fluid/tests/unittests/test_operator_desc.py
+1
-4
未找到文件。
paddle/fluid/operators/mul_mkldnn_op.cc
已删除
100644 → 0
浏览文件 @
654f5d3c
/* 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 "mkldnn.hpp"
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/operators/mul_op.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/mkldnn_helper.h"
namespace
paddle
{
namespace
operators
{
using
paddle
::
framework
::
Tensor
;
using
paddle
::
platform
::
MKLDNNDeviceContext
;
template
<
typename
Format
=
mkldnn
::
memory
::
format
>
mkldnn
::
memory
::
desc
type
(
const
std
::
vector
<
int
>&
dims
,
Format
&&
f
)
{
return
platform
::
MKLDNNMemDesc
(
dims
,
mkldnn
::
memory
::
data_type
::
f32
,
f
);
}
template
<
typename
T
>
class
MulMKLDNNOpKernel
:
public
paddle
::
framework
::
OpKernel
<
T
>
{
void
Compute
(
const
paddle
::
framework
::
ExecutionContext
&
ctx
)
const
override
{
PADDLE_ENFORCE
(
paddle
::
platform
::
is_cpu_place
(
ctx
.
GetPlace
()),
"It must use CPUPlace."
);
auto
&
dev_ctx
=
ctx
.
template
device_context
<
MKLDNNDeviceContext
>();
auto
mkldnn_engine
=
dev_ctx
.
GetEngine
();
auto
input
=
ctx
.
Input
<
Tensor
>
(
"X"
);
auto
weight
=
ctx
.
Input
<
Tensor
>
(
"Y"
);
PADDLE_ENFORCE
(
input
->
dims
().
size
()
&
(
2
|
4
),
"Input must be with 2 or 4 dimensions, i.e. NC or NCHW"
);
PADDLE_ENFORCE
(
weight
->
dims
().
size
()
&
(
2
|
4
),
"Weights must be with 2 or 4 dimensions, i.e. OI or OIHW"
);
std
::
vector
<
int
>
w_tz
=
paddle
::
framework
::
vectorize2int
(
weight
->
dims
());
std
::
vector
<
int
>
src_tz
=
paddle
::
framework
::
vectorize2int
(
input
->
dims
());
auto
src_md
=
src_tz
.
size
()
!=
2
?
type
(
src_tz
,
mkldnn
::
memory
::
format
::
nchw
)
:
type
({
src_tz
[
0
],
src_tz
[
1
]},
mkldnn
::
memory
::
format
::
nc
);
auto
dst_md
=
type
({
src_tz
[
0
],
w_tz
[
1
]},
mkldnn
::
memory
::
format
::
nc
);
auto
weights_md
=
src_tz
.
size
()
!=
2
?
type
({
w_tz
[
1
],
src_tz
[
1
],
src_tz
[
2
],
src_tz
[
3
]},
mkldnn
::
memory
::
format
::
oihw
)
:
type
({
w_tz
[
1
],
src_tz
[
1
]},
mkldnn
::
memory
::
format
::
oi
);
auto
output
=
ctx
.
Output
<
Tensor
>
(
"Out"
);
T
*
output_data
=
output
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
const
std
::
string
key
=
ctx
.
op
().
Output
(
"Out"
);
const
std
::
string
key_fc_pd
=
key
+
"@mul_pd"
;
const
T
*
input_data
=
input
->
data
<
T
>
();
const
T
*
w_data
=
weight
->
data
<
T
>
();
auto
dst_memory
=
mkldnn
::
memory
({
dst_md
,
mkldnn_engine
},
output_data
);
auto
src_memory
=
mkldnn
::
memory
({
src_md
,
mkldnn_engine
},
platform
::
to_void_cast
(
input_data
));
auto
weights_memory
=
mkldnn
::
memory
({
weights_md
,
mkldnn_engine
},
platform
::
to_void_cast
(
w_data
));
auto
pd
=
platform
::
MKLDNNFwdPrimitiveDesc
<
mkldnn
::
inner_product_forward
>
(
mkldnn_engine
,
src_md
,
weights_md
,
dst_md
);
dev_ctx
.
SetBlob
(
key_fc_pd
,
pd
);
auto
forward
=
mkldnn
::
inner_product_forward
(
*
pd
,
src_memory
,
weights_memory
,
dst_memory
);
std
::
vector
<
mkldnn
::
primitive
>
pipeline
=
{
forward
};
mkldnn
::
stream
(
mkldnn
::
stream
::
kind
::
eager
).
submit
(
pipeline
).
wait
();
}
};
template
<
typename
T
>
class
MulMKLDNNGradOpKernel
:
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."
);
auto
&
dev_ctx
=
ctx
.
template
device_context
<
MKLDNNDeviceContext
>();
auto
mkldnn_engine
=
dev_ctx
.
GetEngine
();
const
Tensor
*
input
=
ctx
.
Input
<
Tensor
>
(
"X"
);
const
Tensor
*
w
=
ctx
.
Input
<
Tensor
>
(
"Y"
);
const
Tensor
*
out_grad
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
Tensor
*
input_grad
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
Tensor
*
w_grad
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
const
std
::
string
key
=
ctx
.
op
().
Input
(
"Out"
);
const
std
::
string
key_fc_pd
=
key
+
"@mul_pd"
;
const
T
*
input_data
=
input
->
data
<
T
>
();
const
T
*
w_data
=
w
->
data
<
T
>
();
const
T
*
out_grad_data
=
out_grad
->
data
<
T
>
();
T
*
input_grad_data
=
nullptr
;
T
*
w_grad_data
=
nullptr
;
if
(
input_grad
)
{
input_grad_data
=
input_grad
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
}
if
(
w_grad
)
{
w_grad_data
=
w_grad
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
}
std
::
vector
<
int
>
src_tz
=
paddle
::
framework
::
vectorize2int
(
input
->
dims
());
std
::
vector
<
int
>
w_tz
=
paddle
::
framework
::
vectorize2int
(
w
->
dims
());
auto
src_md
=
src_tz
.
size
()
!=
2
?
type
(
src_tz
,
mkldnn
::
memory
::
format
::
nchw
)
:
type
({
src_tz
[
0
],
src_tz
[
1
]},
mkldnn
::
memory
::
format
::
nc
);
auto
dst_md
=
type
({
src_tz
[
0
],
w_tz
[
1
]},
mkldnn
::
memory
::
format
::
nc
);
auto
weights_md
=
src_tz
.
size
()
!=
2
?
type
({
w_tz
[
1
],
src_tz
[
1
],
src_tz
[
2
],
src_tz
[
3
]},
mkldnn
::
memory
::
format
::
oihw
)
:
type
({
w_tz
[
1
],
src_tz
[
1
]},
mkldnn
::
memory
::
format
::
oi
);
auto
src_memory
=
mkldnn
::
memory
({
src_md
,
mkldnn_engine
},
platform
::
to_void_cast
(
input_data
));
auto
dst_memory
=
mkldnn
::
memory
({
dst_md
,
mkldnn_engine
},
platform
::
to_void_cast
(
out_grad_data
));
auto
weight_memory
=
mkldnn
::
memory
({
weights_md
,
mkldnn_engine
},
platform
::
to_void_cast
(
w_data
));
auto
pd
=
std
::
static_pointer_cast
<
mkldnn
::
inner_product_forward
::
primitive_desc
>
(
dev_ctx
.
GetBlob
(
key_fc_pd
));
PADDLE_ENFORCE
(
pd
!=
nullptr
,
"Fail to find pd in device context"
);
if
(
w_grad
)
{
auto
weights_grad_memory
=
mkldnn
::
memory
(
{
weights_md
,
mkldnn_engine
},
platform
::
to_void_cast
(
w_grad_data
));
auto
bwd_weight_pd
=
platform
::
MKLDNNBwdPrimitiveDesc
<
mkldnn
::
inner_product_backward_weights
>
(
mkldnn_engine
,
*
pd
,
src_md
,
weights_md
,
dst_md
);
auto
bwd_weights_prim
=
mkldnn
::
inner_product_backward_weights
(
bwd_weight_pd
,
src_memory
,
dst_memory
,
weights_grad_memory
);
std
::
vector
<
mkldnn
::
primitive
>
pipeline
{
bwd_weights_prim
};
mkldnn
::
stream
(
mkldnn
::
stream
::
kind
::
eager
).
submit
(
pipeline
).
wait
();
}
if
(
input_grad
)
{
auto
src_grad_memory
=
mkldnn
::
memory
(
{
src_md
,
mkldnn_engine
},
platform
::
to_void_cast
(
input_grad_data
));
auto
bwd_data_pd
=
platform
::
MKLDNNBwdPrimitiveDesc
<
mkldnn
::
inner_product_backward_data
>
(
mkldnn_engine
,
*
pd
,
src_md
,
weights_md
,
dst_md
);
auto
bwd_data_prim
=
mkldnn
::
inner_product_backward_data
(
bwd_data_pd
,
dst_memory
,
weight_memory
,
src_grad_memory
);
std
::
vector
<
mkldnn
::
primitive
>
pipeline
{
bwd_data_prim
};
mkldnn
::
stream
(
mkldnn
::
stream
::
kind
::
eager
).
submit
(
pipeline
).
wait
();
}
}
};
}
// namespace operators
}
// namespace paddle
REGISTER_OP_KERNEL
(
mul
,
MKLDNN
,
::
paddle
::
platform
::
CPUPlace
,
paddle
::
operators
::
MulMKLDNNOpKernel
<
float
>
);
REGISTER_OP_KERNEL
(
mul_grad
,
MKLDNN
,
::
paddle
::
platform
::
CPUPlace
,
paddle
::
operators
::
MulMKLDNNGradOpKernel
<
float
>
);
paddle/fluid/operators/mul_op.cc
浏览文件 @
30d32035
...
...
@@ -16,10 +16,6 @@ limitations under the License. */
#include <string>
#include <vector>
#ifdef PADDLE_WITH_MKLDNN
#include "paddle/fluid/platform/mkldnn_helper.h"
#endif
namespace
paddle
{
namespace
operators
{
...
...
@@ -76,22 +72,6 @@ class MulOp : public framework::OperatorWithKernel {
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
(
output_dims
));
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
}
private:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
framework
::
LibraryType
library
{
framework
::
LibraryType
::
kPlain
};
#ifdef PADDLE_WITH_MKLDNN
if
(
library
==
framework
::
LibraryType
::
kPlain
&&
platform
::
CanMKLDNNBeUsed
(
ctx
))
{
library
=
framework
::
LibraryType
::
kMKLDNN
;
}
#endif
framework
::
DataLayout
layout
{
framework
::
DataLayout
::
kAnyLayout
};
return
framework
::
OpKernelType
(
framework
::
ToDataType
(
ctx
.
Input
<
Tensor
>
(
"X"
)
->
type
()),
ctx
.
GetPlace
(),
layout
,
library
);
}
};
class
MulOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
...
...
@@ -120,9 +100,6 @@ class MulOpMaker : public framework::OpProtoAndCheckerMaker {
)DOC"
)
.
SetDefault
(
1
)
.
EqualGreaterThan
(
1
);
AddAttr
<
bool
>
(
"use_mkldnn"
,
"(bool, default false) Only used in mkldnn kernel"
)
.
SetDefault
(
false
);
AddAttr
<
int
>
(
"y_num_col_dims"
,
R"DOC((int, default 1), The mul_op can take tensors with more than two,
...
...
@@ -177,22 +154,6 @@ class MulGradOp : public framework::OperatorWithKernel {
ctx
->
SetOutputDim
(
y_grad_name
,
y_dims
);
}
}
private:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
framework
::
LibraryType
library
{
framework
::
LibraryType
::
kPlain
};
#ifdef PADDLE_WITH_MKLDNN
if
(
library
==
framework
::
LibraryType
::
kPlain
&&
platform
::
CanMKLDNNBeUsed
(
ctx
))
{
library
=
framework
::
LibraryType
::
kMKLDNN
;
}
#endif
framework
::
DataLayout
layout
{
framework
::
DataLayout
::
kAnyLayout
};
return
framework
::
OpKernelType
(
framework
::
ToDataType
(
ctx
.
Input
<
Tensor
>
(
"X"
)
->
type
()),
ctx
.
GetPlace
(),
layout
,
library
);
}
};
}
// namespace operators
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
30d32035
...
...
@@ -177,11 +177,8 @@ def fc(input,
inputs
=
{
"X"
:
input_var
,
"Y"
:
w
},
outputs
=
{
"Out"
:
tmp
},
attrs
=
{
"x_num_col_dims"
:
num_flatten_dims
,
"y_num_col_dims"
:
1
,
"use_mkldnn"
:
use_mkldnn
})
attrs
=
{
"x_num_col_dims"
:
num_flatten_dims
,
"y_num_col_dims"
:
1
})
mul_results
.
append
(
tmp
)
if
len
(
mul_results
)
==
1
:
...
...
@@ -3929,10 +3926,10 @@ def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None):
Bilinear interpolation is an extension of linear interpolation for
interpolating functions of two variables (e.g. H-direction and
W-direction in this layer) on a rectilinear 2D grid.
For details, please refer to Wikipedia:
https://en.wikipedia.org/wiki/Bilinear_interpolation
Args:
input (Variable): The input tensor of bilinear interpolation,
This is a 4-D tensor of the shape
...
...
@@ -3950,7 +3947,7 @@ def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None):
Returns:
out (Variable): The output is a 4-D tensor of the shape
(num_batches, channls, out_h, out_w).
Examples:
.. code-block:: python
...
...
python/paddle/fluid/tests/unittests/test_mul_mkldnn_op.py
已删除
100644 → 0
浏览文件 @
654f5d3c
# 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.
import
unittest
from
test_mul_op
import
TestMulOp
,
TestMulOp2
,
TestFP16MulOp1
,
TestFP16MulOp2
class
TestMKLDNNMulOp
(
TestMulOp
):
def
init_op_test
(
self
):
super
(
TestMKLDNNMulOp
,
self
).
setUp
()
self
.
attrs
=
{
"use_mkldnn"
:
True
}
class
TestMKLDNNMulOp2
(
TestMulOp2
):
def
init_op_test
(
self
):
super
(
TestMKLDNNMulOp2
,
self
).
setUp
()
self
.
attrs
=
{
"use_mkldnn"
:
True
}
class
TestMKLDNNFP16MulOp1
(
TestFP16MulOp1
):
def
init_op_test
(
self
):
super
(
TestMKLDNNFP16MulOp1
,
self
).
setUp
()
self
.
attrs
=
{
"use_mkldnn"
:
True
}
class
TestMKLDNNFP16MulOp2
(
TestFP16MulOp2
):
def
init_op_test
(
self
):
super
(
TestMKLDNNFP16MulOp2
,
self
).
setUp
()
self
.
attrs
=
{
"use_mkldnn"
:
True
}
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_mul_op.py
浏览文件 @
30d32035
...
...
@@ -21,12 +21,10 @@ from op_test import OpTest
class
TestMulOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"mul"
self
.
use_mkldnn
=
False
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
32
,
84
)).
astype
(
"float32"
),
'Y'
:
np
.
random
.
random
((
84
,
100
)).
astype
(
"float32"
)
}
self
.
attrs
=
{
'use_mkldnn'
:
self
.
use_mkldnn
}
self
.
outputs
=
{
'Out'
:
np
.
dot
(
self
.
inputs
[
'X'
],
self
.
inputs
[
'Y'
])}
def
test_check_output
(
self
):
...
...
@@ -47,16 +45,11 @@ class TestMulOp(OpTest):
class
TestMulOp2
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"mul"
self
.
use_mkldnn
=
False
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
15
,
4
,
12
,
10
)).
astype
(
"float32"
),
'Y'
:
np
.
random
.
random
((
4
,
30
,
8
,
2
,
9
)).
astype
(
"float32"
)
}
self
.
attrs
=
{
'x_num_col_dims'
:
2
,
'y_num_col_dims'
:
2
,
'use_mkldnn'
:
self
.
use_mkldnn
}
self
.
attrs
=
{
'x_num_col_dims'
:
2
,
'y_num_col_dims'
:
2
}
result
=
np
.
dot
(
self
.
inputs
[
'X'
].
reshape
(
15
*
4
,
12
*
10
),
self
.
inputs
[
'Y'
].
reshape
(
4
*
30
,
8
*
2
*
9
))
result
=
result
.
reshape
(
15
,
4
,
8
,
2
,
9
)
...
...
@@ -80,11 +73,9 @@ class TestMulOp2(OpTest):
class
TestFP16MulOp1
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"mul"
self
.
use_mkldnn
=
False
x
=
np
.
random
.
random
((
32
,
84
)).
astype
(
"float16"
)
y
=
np
.
random
.
random
((
84
,
100
)).
astype
(
"float16"
)
self
.
inputs
=
{
'X'
:
x
.
view
(
np
.
uint16
),
'Y'
:
y
.
view
(
np
.
uint16
)}
self
.
attrs
=
{
'use_mkldnn'
:
self
.
use_mkldnn
}
self
.
outputs
=
{
'Out'
:
np
.
dot
(
x
,
y
)}
def
test_check_output
(
self
):
...
...
@@ -97,15 +88,10 @@ class TestFP16MulOp1(OpTest):
class
TestFP16MulOp2
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"mul"
self
.
use_mkldnn
=
False
x
=
np
.
random
.
random
((
15
,
4
,
12
,
10
)).
astype
(
"float16"
)
y
=
np
.
random
.
random
((
4
,
30
,
8
,
2
,
9
)).
astype
(
"float16"
)
self
.
inputs
=
{
'X'
:
x
.
view
(
np
.
uint16
),
'Y'
:
y
.
view
(
np
.
uint16
)}
self
.
attrs
=
{
'x_num_col_dims'
:
2
,
'y_num_col_dims'
:
2
,
'use_mkldnn'
:
self
.
use_mkldnn
}
self
.
attrs
=
{
'x_num_col_dims'
:
2
,
'y_num_col_dims'
:
2
}
result
=
np
.
dot
(
x
.
reshape
(
15
*
4
,
12
*
10
),
y
.
reshape
(
4
*
30
,
8
*
2
*
9
))
result
=
result
.
reshape
(
15
,
4
,
8
,
2
,
9
)
...
...
python/paddle/fluid/tests/unittests/test_operator_desc.py
浏览文件 @
30d32035
...
...
@@ -63,10 +63,7 @@ class TestOperator(unittest.TestCase):
self
.
assertEqual
(
mul_op
.
output
(
"Out"
),
[
"mul.out"
])
self
.
assertEqual
(
set
(
mul_op
.
attr_names
),
set
([
"x_num_col_dims"
,
"y_num_col_dims"
,
"use_mkldnn"
,
"op_role"
,
"op_role_var"
]))
set
([
"x_num_col_dims"
,
"y_num_col_dims"
,
"op_role"
,
"op_role_var"
]))
self
.
assertEqual
(
mul_op
.
has_attr
(
"x_num_col_dims"
),
True
)
self
.
assertEqual
(
mul_op
.
attr_type
(
"x_num_col_dims"
),
core
.
AttrType
.
INT
)
self
.
assertEqual
(
mul_op
.
attr
(
"x_num_col_dims"
),
1
)
...
...
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