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体验新版 GitCode,发现更多精彩内容 >>
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11fb8a1c
编写于
8月 31, 2020
作者:
G
GaoWei8
提交者:
GitHub
8月 31, 2020
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差异文件
Refine cudnn softmax (#25757)
* refine cudnn softmax
上级
885c61f0
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
155 addition
and
45 deletion
+155
-45
paddle/fluid/operators/softmax_cudnn_op.cu.cc
paddle/fluid/operators/softmax_cudnn_op.cu.cc
+68
-38
paddle/fluid/operators/softmax_op.cc
paddle/fluid/operators/softmax_op.cc
+0
-7
python/paddle/fluid/tests/unittests/test_softmax_op.py
python/paddle/fluid/tests/unittests/test_softmax_op.py
+87
-0
未找到文件。
paddle/fluid/operators/softmax_cudnn_op.cu.cc
浏览文件 @
11fb8a1c
...
@@ -12,60 +12,90 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
...
@@ -12,60 +12,90 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
See the License for the specific language governing permissions and
limitations under the License. */
limitations under the License. */
#include "paddle/fluid/operators/math/softmax.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/softmax_op.h"
#include "paddle/fluid/platform/cudnn_desc.h"
#include "paddle/fluid/platform/cudnn_helper.h"
namespace
paddle
{
namespace
paddle
{
namespace
operators
{
namespace
operators
{
using
ScopedTensorDescriptor
=
platform
::
ScopedTensorDescriptor
;
using
DataLayout
=
platform
::
DataLayout
;
using
Tensor
=
framework
::
Tensor
;
using
Tensor
=
framework
::
Tensor
;
static
inline
int
SizeOutAxis
(
const
int
axis
,
DDim
dims
)
{
int
size
=
1
;
for
(
int
i
=
axis
+
1
;
i
<
dims
.
size
();
i
++
)
{
size
*=
dims
[
i
];
}
return
size
;
}
template
<
typename
T
>
template
<
typename
T
>
class
SoftmaxCUDNNKernel
:
public
framework
::
OpKernel
<
T
>
{
class
SoftmaxCUDNNKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
*
X
=
context
.
Input
<
Tensor
>
(
"X"
);
auto
*
x
=
ctx
.
Input
<
Tensor
>
(
"X"
);
auto
*
Out
=
context
.
Output
<
Tensor
>
(
"Out"
);
auto
*
out
=
ctx
.
Output
<
Tensor
>
(
"Out"
);
out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
// allocate memory on device.
auto
*
out_data
=
out
->
data
<
T
>
();
Out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
dims
=
x
->
dims
();
auto
dims
=
X
->
dims
();
const
int
rank
=
dims
.
size
();
auto
flattened_dims
=
framework
::
flatten_to_2d
(
dims
,
dims
.
size
()
-
1
);
const
int
axis
=
CanonicalAxis
(
ctx
.
Attr
<
int
>
(
"axis"
),
rank
);
framework
::
LoDTensor
flattened_x
;
const
int
dim
=
dims
[
axis
];
framework
::
LoDTensor
flattened_out
;
const
int
N
=
SizeToAxis
(
axis
,
dims
);
flattened_x
.
ShareDataWith
(
*
X
).
Resize
(
flattened_dims
);
const
int
D
=
SizeOutAxis
(
axis
,
dims
);
flattened_out
.
ShareDataWith
(
*
Out
).
Resize
(
flattened_dims
);
ScopedTensorDescriptor
desc
;
math
::
SoftmaxCUDNNFunctor
<
T
>
()(
std
::
vector
<
int
>
tensor_dims
=
{
N
,
dim
,
D
,
1
};
context
.
template
device_context
<
platform
::
CUDADeviceContext
>(),
DataLayout
layout
=
DataLayout
::
kNCHW
;
&
flattened_x
,
&
flattened_out
);
cudnnTensorDescriptor_t
desc_
=
desc
.
descriptor
<
T
>
(
layout
,
tensor_dims
);
auto
&
dev_ctx
=
ctx
.
template
device_context
<
platform
::
CUDADeviceContext
>();
auto
handle
=
dev_ctx
.
cudnn_handle
();
auto
mode
=
axis
==
rank
-
1
?
CUDNN_SOFTMAX_MODE_INSTANCE
:
CUDNN_SOFTMAX_MODE_CHANNEL
;
PADDLE_ENFORCE_CUDA_SUCCESS
(
platform
::
dynload
::
cudnnSoftmaxForward
(
handle
,
CUDNN_SOFTMAX_ACCURATE
,
mode
,
platform
::
CudnnDataType
<
T
>::
kOne
(),
desc_
,
x
->
data
<
T
>
(),
platform
::
CudnnDataType
<
T
>::
kZero
(),
desc_
,
out_data
));
}
}
};
};
template
<
typename
T
>
template
<
typename
T
>
class
SoftmaxGradCUDNNKernel
:
public
framework
::
OpKernel
<
T
>
{
class
SoftmaxGradCUDNNKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
*
Out
=
context
.
Input
<
Tensor
>
(
"Out"
);
auto
*
out
=
ctx
.
Input
<
Tensor
>
(
"Out"
);
auto
*
dOut
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
dout
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
dX
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
dx
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
dx
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
// allocate memory on device.
auto
*
dx_data
=
dx
->
data
<
T
>
();
dX
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
dims
=
out
->
dims
();
auto
dims
=
Out
->
dims
();
const
int
rank
=
dims
.
size
();
auto
flattened_dims
=
framework
::
flatten_to_2d
(
dims
,
dims
.
size
()
-
1
);
const
int
axis
=
CanonicalAxis
(
ctx
.
Attr
<
int
>
(
"axis"
),
rank
);
framework
::
LoDTensor
flattened_out
;
const
int
dim
=
dims
[
axis
];
framework
::
LoDTensor
flattened_d_out
;
const
int
N
=
SizeToAxis
(
axis
,
dims
);
framework
::
LoDTensor
flattened_d_x
;
const
int
D
=
SizeOutAxis
(
axis
,
dims
);
flattened_out
.
ShareDataWith
(
*
Out
).
Resize
(
flattened_dims
);
flattened_d_out
.
ShareDataWith
(
*
dOut
).
Resize
(
flattened_dims
);
ScopedTensorDescriptor
desc
;
flattened_d_x
.
ShareDataWith
(
*
dX
).
Resize
(
flattened_dims
);
std
::
vector
<
int
>
tensor_dims
=
{
N
,
dim
,
D
,
1
};
DataLayout
layout
=
DataLayout
::
kNCHW
;
math
::
SoftmaxGradCUDNNFunctor
<
T
>
()(
cudnnTensorDescriptor_t
desc_
=
desc
.
descriptor
<
T
>
(
layout
,
tensor_dims
);
context
.
template
device_context
<
platform
::
CUDADeviceContext
>(),
&
flattened_out
,
&
flattened_d_out
,
&
flattened_d_x
);
auto
&
dev_ctx
=
ctx
.
template
device_context
<
platform
::
CUDADeviceContext
>();
auto
handle
=
dev_ctx
.
cudnn_handle
();
auto
mode
=
axis
==
rank
-
1
?
CUDNN_SOFTMAX_MODE_INSTANCE
:
CUDNN_SOFTMAX_MODE_CHANNEL
;
PADDLE_ENFORCE_CUDA_SUCCESS
(
platform
::
dynload
::
cudnnSoftmaxBackward
(
handle
,
CUDNN_SOFTMAX_ACCURATE
,
mode
,
platform
::
CudnnDataType
<
T
>::
kOne
(),
desc_
,
out
->
data
<
T
>
(),
desc_
,
dout
->
data
<
T
>
(),
platform
::
CudnnDataType
<
T
>::
kZero
(),
desc_
,
dx_data
));
}
}
};
};
...
...
paddle/fluid/operators/softmax_op.cc
浏览文件 @
11fb8a1c
...
@@ -53,13 +53,6 @@ class SoftmaxOp : public framework::OperatorWithKernel {
...
@@ -53,13 +53,6 @@ class SoftmaxOp : public framework::OperatorWithKernel {
"Attr(axis) value should be in range [-R, R-1], "
"Attr(axis) value should be in range [-R, R-1], "
"R is the rank of Input(X)."
));
"R is the rank of Input(X)."
));
auto
use_cudnn
=
ctx
->
Attrs
().
Get
<
bool
>
(
"use_cudnn"
);
if
(
axis
!=
rank_x
-
1
&&
axis
!=
-
1
)
{
PADDLE_ENFORCE_EQ
(
use_cudnn
,
false
,
platform
::
errors
::
InvalidArgument
(
"CUDNN kernel only support axis as -1."
));
}
ctx
->
SetOutputDim
(
"Out"
,
ctx
->
GetInputDim
(
"X"
));
ctx
->
SetOutputDim
(
"Out"
,
ctx
->
GetInputDim
(
"X"
));
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
}
}
...
...
python/paddle/fluid/tests/unittests/test_softmax_op.py
浏览文件 @
11fb8a1c
...
@@ -153,16 +153,103 @@ class TestSoftmaxCUDNNOp2(TestSoftmaxCUDNNOp):
...
@@ -153,16 +153,103 @@ class TestSoftmaxCUDNNOp2(TestSoftmaxCUDNNOp):
return
[
2
,
3
,
4
,
5
]
return
[
2
,
3
,
4
,
5
]
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
(),
"core is not compiled with CUDA"
)
class
TestSoftmaxCUDNNOp3
(
TestSoftmaxCUDNNOp
):
def
get_x_shape
(
self
):
return
[
2
,
3
,
4
,
5
]
def
get_axis
(
self
):
return
0
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
(),
"core is not compiled with CUDA"
)
class
TestSoftmaxCUDNNOp4
(
TestSoftmaxCUDNNOp
):
def
get_x_shape
(
self
):
return
[
2
,
3
,
4
,
5
]
def
get_axis
(
self
):
return
1
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
(),
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
(),
"core is not compiled with CUDA"
)
"core is not compiled with CUDA"
)
class
TestSoftmaxCUDNNOp5
(
TestSoftmaxCUDNNOp
):
class
TestSoftmaxCUDNNOp5
(
TestSoftmaxCUDNNOp
):
def
get_x_shape
(
self
):
def
get_x_shape
(
self
):
return
[
2
,
3
,
4
,
5
]
return
[
2
,
3
,
4
,
5
]
def
get_axis
(
self
):
return
2
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
(),
"core is not compiled with CUDA"
)
class
TestSoftmaxCUDNNOp6
(
TestSoftmaxCUDNNOp
):
def
get_x_shape
(
self
):
return
[
2
,
3
,
4
,
5
]
def
get_axis
(
self
):
def
get_axis
(
self
):
return
3
return
3
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
(),
"core is not compiled with CUDA"
)
class
TestSoftmaxCUDNNOp7
(
TestSoftmaxCUDNNOp
):
def
get_x_shape
(
self
):
return
[
2
,
3
,
4
,
5
,
6
]
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
(),
"core is not compiled with CUDA"
)
class
TestSoftmaxCUDNNOp8
(
TestSoftmaxCUDNNOp
):
def
get_x_shape
(
self
):
return
[
2
,
3
,
4
,
5
,
6
]
def
get_axis
(
self
):
return
0
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
(),
"core is not compiled with CUDA"
)
class
TestSoftmaxCUDNNOp9
(
TestSoftmaxCUDNNOp
):
def
get_x_shape
(
self
):
return
[
2
,
3
,
4
,
5
,
6
]
def
get_axis
(
self
):
return
1
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
(),
"core is not compiled with CUDA"
)
class
TestSoftmaxCUDNNOp10
(
TestSoftmaxCUDNNOp
):
def
get_x_shape
(
self
):
return
[
2
,
3
,
4
,
5
,
6
]
def
get_axis
(
self
):
return
2
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
(),
"core is not compiled with CUDA"
)
class
TestSoftmaxCUDNNOp11
(
TestSoftmaxCUDNNOp
):
def
get_x_shape
(
self
):
return
[
2
,
3
,
4
,
5
,
6
]
def
get_axis
(
self
):
return
3
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
(),
"core is not compiled with CUDA"
)
class
TestSoftmaxCUDNNOp12
(
TestSoftmaxCUDNNOp
):
def
get_x_shape
(
self
):
return
[
2
,
3
,
4
,
5
,
6
]
def
get_axis
(
self
):
return
4
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
(),
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
(),
"core is not compiled with CUDA"
)
"core is not compiled with CUDA"
)
class
TestSoftmaxFP16Op
(
TestSoftmaxOp
):
class
TestSoftmaxFP16Op
(
TestSoftmaxOp
):
...
...
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