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体验新版 GitCode,发现更多精彩内容 >>
提交
a2657fea
编写于
9月 29, 2017
作者:
C
Cao Ying
提交者:
GitHub
9月 29, 2017
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差异文件
Merge pull request #4472 from Xreki/core_add_sequence_softmax_op
Add sequence softmax operator.
上级
7cc5ae99
8bafdda0
变更
12
隐藏空白更改
内联
并排
Showing
12 changed file
with
355 addition
and
77 deletion
+355
-77
paddle/operators/CMakeLists.txt
paddle/operators/CMakeLists.txt
+2
-2
paddle/operators/math/CMakeLists.txt
paddle/operators/math/CMakeLists.txt
+6
-8
paddle/operators/math/softmax.cc
paddle/operators/math/softmax.cc
+10
-9
paddle/operators/math/softmax.cu
paddle/operators/math/softmax.cu
+10
-9
paddle/operators/math/softmax.h
paddle/operators/math/softmax.h
+40
-9
paddle/operators/mul_op.cc
paddle/operators/mul_op.cc
+17
-15
paddle/operators/sequence_pool_op.cc
paddle/operators/sequence_pool_op.cc
+2
-2
paddle/operators/sequence_softmax_op.cc
paddle/operators/sequence_softmax_op.cc
+103
-0
paddle/operators/sequence_softmax_op.cu
paddle/operators/sequence_softmax_op.cu
+25
-0
paddle/operators/sequence_softmax_op.h
paddle/operators/sequence_softmax_op.h
+94
-0
paddle/operators/softmax_op.h
paddle/operators/softmax_op.h
+8
-23
python/paddle/v2/framework/tests/test_sequence_softmax_op.py
python/paddle/v2/framework/tests/test_sequence_softmax_op.py
+38
-0
未找到文件。
paddle/operators/CMakeLists.txt
浏览文件 @
a2657fea
...
...
@@ -101,8 +101,8 @@ set(DEPS_OPS
op_library
(
recurrent_op SRCS recurrent_op.cc rnn/recurrent_op_utils.cc
DEPS framework_proto tensor net_op
)
op_library
(
cond_op SRCS cond_op.cc DEPS framework_proto tensor operator net_op
)
op_library
(
cross_entropy_op DEPS cross_entropy
_function
)
op_library
(
softmax_with_cross_entropy_op DEPS cross_entropy
_function softmax_function
)
op_library
(
cross_entropy_op DEPS cross_entropy
)
op_library
(
softmax_with_cross_entropy_op DEPS cross_entropy
softmax
)
list
(
REMOVE_ITEM GENERAL_OPS
${
DEPS_OPS
}
)
foreach
(
src
${
GENERAL_OPS
}
)
...
...
paddle/operators/math/CMakeLists.txt
浏览文件 @
a2657fea
if
(
WITH_GPU
)
nv_library
(
math_function SRCS math_function.cc math_function.cu im2col.cc
im2col.cu DEPS cblas device_context operator
)
im2col.cu DEPS cblas device_context operator
)
nv_test
(
math_function_test SRCS math_function_test.cc DEPS math_function tensor
)
nv_library
(
softmax_function SRCS softmax.cc softmax.cu
DEPS operator
)
nv_library
(
cross_entropy_function SRCS cross_entropy.cc cross_entropy.cu
DEPS operator
)
nv_library
(
softmax SRCS softmax.cc softmax.cu DEPS operator
)
nv_library
(
cross_entropy SRCS cross_entropy.cc cross_entropy.cu DEPS operator
)
else
()
cc_library
(
math_function SRCS math_function.cc im2col.cc
DEPS cblas device_context operator
)
DEPS cblas device_context operator
)
cc_test
(
math_function_test SRCS math_function_test.cc DEPS math_function tensor
)
cc_library
(
softmax
_function
SRCS softmax.cc DEPS operator
)
cc_library
(
cross_entropy
_function
SRCS cross_entropy.cc DEPS operator
)
cc_library
(
softmax SRCS softmax.cc DEPS operator
)
cc_library
(
cross_entropy SRCS cross_entropy.cc DEPS operator
)
endif
()
cc_test
(
im2col_test SRCS im2col_test.cc DEPS math_function tensor
)
paddle/operators/math/softmax.cc
浏览文件 @
a2657fea
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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
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
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. */
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/operators/math/softmax.h"
...
...
@@ -19,6 +19,7 @@ namespace operators {
namespace
math
{
template
class
SoftmaxFunctor
<
platform
::
CPUPlace
,
float
>;
template
class
SoftmaxGradFunctor
<
platform
::
CPUPlace
,
float
>;
}
// namespace math
}
// namespace operators
...
...
paddle/operators/math/softmax.cu
浏览文件 @
a2657fea
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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
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
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. */
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. */
#define EIGEN_USE_GPU
...
...
@@ -21,6 +21,7 @@ namespace operators {
namespace
math
{
template
class
SoftmaxFunctor
<
platform
::
GPUPlace
,
float
>;
template
class
SoftmaxGradFunctor
<
platform
::
GPUPlace
,
float
>;
}
// namespace math
}
// namespace operators
...
...
paddle/operators/math/softmax.h
浏览文件 @
a2657fea
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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
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
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. */
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. */
#pragma once
#include "paddle/framework/eigen.h"
...
...
@@ -68,6 +68,37 @@ class SoftmaxFunctor {
.
broadcast
(
one_by_class
));
}
};
template
<
typename
Place
,
typename
T
>
class
SoftmaxGradFunctor
{
public:
void
operator
()(
const
platform
::
DeviceContext
&
context
,
const
framework
::
Tensor
*
y
,
const
framework
::
Tensor
*
y_grad
,
framework
::
Tensor
*
x_grad
)
{
auto
softmax
=
EigenMatrix
<
T
>::
From
(
*
y
);
auto
softmax_grad
=
EigenMatrix
<
T
>::
From
(
*
y_grad
);
auto
logits_grad
=
EigenMatrix
<
T
>::
From
(
*
x_grad
);
const
int
kBatchDim
=
0
;
const
int
kClassDim
=
1
;
const
int
batch_size
=
softmax
.
dimension
(
kBatchDim
);
const
int
num_classes
=
softmax
.
dimension
(
kClassDim
);
Eigen
::
DSizes
<
int
,
1
>
along_class
(
kClassDim
);
Eigen
::
DSizes
<
int
,
2
>
batch_by_one
(
batch_size
,
1
);
Eigen
::
DSizes
<
int
,
2
>
one_by_class
(
1
,
num_classes
);
auto
dot
=
(
softmax
*
softmax_grad
)
.
sum
(
along_class
)
.
eval
()
.
reshape
(
batch_by_one
)
.
broadcast
(
one_by_class
);
logits_grad
.
device
(
*
context
.
GetEigenDevice
<
Place
>
())
=
(
softmax_grad
-
dot
)
*
softmax
;
}
};
}
// namespace math
}
// namespace operators
}
// namespace paddle
paddle/operators/mul_op.cc
浏览文件 @
a2657fea
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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
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
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. */
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/operators/mul_op.h"
...
...
@@ -35,12 +35,14 @@ class MulOp : public framework::OperatorWithKernel {
int
x_num_col_dims
=
ctx
->
Attrs
().
Get
<
int
>
(
"x_num_col_dims"
);
int
y_num_col_dims
=
ctx
->
Attrs
().
Get
<
int
>
(
"y_num_col_dims"
);
PADDLE_ENFORCE
(
x_dims
.
size
()
>
x_num_col_dims
,
"The rank of input tensor X should be larger than "
"`mul_op`'s `x_num_col_dims`."
);
PADDLE_ENFORCE
(
y_dims
.
size
()
>
y_num_col_dims
,
"The rank of input tensor Y should be larger than "
"`mul_op`'s `y_num_col_dims`."
);
PADDLE_ENFORCE_GT
(
x_dims
.
size
(),
x_num_col_dims
,
"The input tensor X's rank of MulOp should be larger than "
"x_num_col_dims."
);
PADDLE_ENFORCE_GT
(
y_dims
.
size
(),
y_num_col_dims
,
"The input tensor Y's rank of MulOp should be larger than "
"y_num_col_dims."
);
auto
x_mat_dims
=
framework
::
flatten_to_2d
(
x_dims
,
x_num_col_dims
);
auto
y_mat_dims
=
framework
::
flatten_to_2d
(
y_dims
,
y_num_col_dims
);
...
...
paddle/operators/sequence_pool_op.cc
浏览文件 @
a2657fea
...
...
@@ -24,9 +24,9 @@ class SequencePoolOp : public framework::OperatorWithKernel {
protected:
void
InferShape
(
framework
::
InferShapeContextBase
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of Sequence
Avg
PoolOp should not be null."
);
"Input(X) of SequencePoolOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of Sequence
Avg
PoolOp should not be null."
);
"Output(Out) of SequencePoolOp should not be null."
);
ctx
->
SetOutputDim
(
"Out"
,
ctx
->
GetInputDim
(
"X"
));
}
};
...
...
paddle/operators/sequence_softmax_op.cc
0 → 100644
浏览文件 @
a2657fea
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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/operators/sequence_softmax_op.h"
namespace
paddle
{
namespace
operators
{
class
SequenceSoftmaxOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
void
InferShape
(
framework
::
InferShapeContextBase
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of SequenceSoftmaxOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of SequenceSoftmaxOp should not be null."
);
ctx
->
SetOutputDim
(
"Out"
,
ctx
->
GetInputDim
(
"X"
));
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
}
};
class
SequenceSoftmaxOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
SequenceSoftmaxOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"(LoDTensor) 1-D or 2-D input LoDTensor with the 2-nd dimension "
"of length 1."
);
AddOutput
(
"Out"
,
"(LoDTensor) 1-D or 2-D output LoDTensor with the 2-nd dimension "
"of length 1."
);
AddComment
(
R"DOC(
SequenceSoftmaxOp computes softmax activation among all time-steps for each
sequence. The dimension of each time-step should be 1. Thus, the shape of
input Tensor can be either [N, 1] or [N], where N is the sum of all sequences'
lengths.
Equation:
for i-th sequence in a mini-batch:
Out(X[lod[i]:lod[i+1]], :) =
exp(X[lod[i]:lod[i+1], :]) / sum(exp(X[lod[i]:lod[i+1], :]))
For example, for a mini-batch of 3 sequences with variable-length,
each containing 2, 3, 2 time-steps, the lod of which is [0, 2, 5, 7],
then softmax will be computed among X[0:2, :], X[2:5, :], X[5:7, :]
and N turns out to be 7.
)DOC"
);
}
};
class
SequenceSoftmaxGradOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
void
InferShape
(
framework
::
InferShapeContextBase
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Out"
),
"Input(Out) of SequenceSoftmaxGradOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input(Out@GRAD) of SequenceSoftmaxGradOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of SequenceSoftmaxOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"X"
)),
"Output(X@GRAD) of SequenceSoftmaxOp should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
GetInputDim
(
"Out"
),
ctx
->
GetInputDim
(
framework
::
GradVarName
(
"Out"
)),
"Input(Out) and Input(Out@GRAD) of SequenceSoftmaxGradOp should be of "
"the same shape."
);
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
ctx
->
GetInputDim
(
"X"
));
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP
(
sequence_softmax
,
ops
::
SequenceSoftmaxOp
,
ops
::
SequenceSoftmaxOpMaker
,
sequence_softmax_grad
,
ops
::
SequenceSoftmaxGradOp
);
REGISTER_OP_CPU_KERNEL
(
sequence_softmax
,
ops
::
SequenceSoftmaxKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_OP_CPU_KERNEL
(
sequence_softmax_grad
,
ops
::
SequenceSoftmaxGradKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
paddle/operators/sequence_softmax_op.cu
0 → 100644
浏览文件 @
a2657fea
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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. */
#define EIGEN_USE_GPU
#include "paddle/operators/sequence_softmax_op.h"
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_GPU_KERNEL
(
sequence_softmax
,
ops
::
SequenceSoftmaxKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
)
REGISTER_OP_GPU_KERNEL
(
sequence_softmax_grad
,
ops
::
SequenceSoftmaxGradKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
paddle/operators/sequence_softmax_op.h
0 → 100644
浏览文件 @
a2657fea
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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. */
#pragma once
#include "paddle/framework/eigen.h"
#include "paddle/framework/op_registry.h"
#include "paddle/operators/math/softmax.h"
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
using
LoDTensor
=
framework
::
LoDTensor
;
template
<
typename
Place
,
typename
T
>
class
SequenceSoftmaxKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
*
x
=
ctx
.
Input
<
LoDTensor
>
(
"X"
);
auto
*
out
=
ctx
.
Output
<
LoDTensor
>
(
"Out"
);
auto
lod
=
x
->
lod
();
auto
dims
=
x
->
dims
();
const
size_t
level
=
lod
.
size
()
-
1
;
PADDLE_ENFORCE_EQ
(
dims
[
0
],
static_cast
<
int64_t
>
(
lod
[
level
].
back
()),
"The first dimension of Input(X) should be equal to the "
"sum of all sequences' lengths."
);
PADDLE_ENFORCE_EQ
(
dims
[
0
],
x
->
numel
(),
"The width of each timestep in Input(X) of "
"SequenceSoftmaxOp should be 1."
);
out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
for
(
int
i
=
0
;
i
<
static_cast
<
int
>
(
lod
[
level
].
size
())
-
1
;
++
i
)
{
int
start_pos
=
static_cast
<
int
>
(
lod
[
level
][
i
]);
int
end_pos
=
static_cast
<
int
>
(
lod
[
level
][
i
+
1
]);
Tensor
x_i
=
x
->
Slice
<
T
>
(
start_pos
,
end_pos
);
Tensor
out_i
=
out
->
Slice
<
T
>
(
start_pos
,
end_pos
);
// Reshape from (end_pos - start_pos) x 1UL to 1UL x (end_pos - start_pos)
framework
::
DDim
dims_i
=
framework
::
make_ddim
({
1UL
,
end_pos
-
start_pos
});
x_i
.
Resize
(
dims_i
);
out_i
.
Resize
(
dims_i
);
math
::
SoftmaxFunctor
<
Place
,
T
>
()(
ctx
.
device_context
(),
&
x_i
,
&
out_i
);
}
}
};
template
<
typename
Place
,
typename
T
>
class
SequenceSoftmaxGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
*
out
=
ctx
.
Input
<
LoDTensor
>
(
"Out"
);
auto
*
out_grad
=
ctx
.
Input
<
LoDTensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
x
=
ctx
.
Input
<
LoDTensor
>
(
"X"
);
auto
*
x_grad
=
ctx
.
Output
<
LoDTensor
>
(
framework
::
GradVarName
(
"X"
));
auto
lod
=
x
->
lod
();
const
size_t
level
=
lod
.
size
()
-
1
;
x_grad
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
for
(
int
i
=
0
;
i
<
static_cast
<
int
>
(
lod
[
level
].
size
())
-
1
;
++
i
)
{
int
start_pos
=
static_cast
<
int
>
(
lod
[
level
][
i
]);
int
end_pos
=
static_cast
<
int
>
(
lod
[
level
][
i
+
1
]);
Tensor
out_i
=
out
->
Slice
<
T
>
(
start_pos
,
end_pos
);
Tensor
out_grad_i
=
out_grad
->
Slice
<
T
>
(
start_pos
,
end_pos
);
Tensor
x_grad_i
=
x_grad
->
Slice
<
T
>
(
start_pos
,
end_pos
);
// Reshape from (end_pos - start_pos) x 1UL to 1UL x (end_pos - start_pos)
framework
::
DDim
dims_i
=
framework
::
make_ddim
({
1UL
,
end_pos
-
start_pos
});
out_i
.
Resize
(
dims_i
);
out_grad_i
.
Resize
(
dims_i
);
x_grad_i
.
Resize
(
dims_i
);
math
::
SoftmaxGradFunctor
<
Place
,
T
>
()(
ctx
.
device_context
(),
&
out_i
,
&
out_grad_i
,
&
x_grad_i
);
}
}
};
}
// namespace operators
}
// namespace paddle
paddle/operators/softmax_op.h
浏览文件 @
a2657fea
...
...
@@ -29,8 +29,8 @@ template <typename Place, typename T>
class
SoftmaxKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
X
=
context
.
Input
<
Tensor
>
(
"X"
);
auto
Y
=
context
.
Output
<
Tensor
>
(
"Y"
);
auto
*
X
=
context
.
Input
<
Tensor
>
(
"X"
);
auto
*
Y
=
context
.
Output
<
Tensor
>
(
"Y"
);
// allocate memory on device.
Y
->
mutable_data
<
T
>
(
context
.
GetPlace
());
...
...
@@ -43,29 +43,14 @@ template <typename Place, typename T>
class
SoftmaxGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
Y
=
context
.
Input
<
Tensor
>
(
"Y"
);
auto
dY
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
auto
dX
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
dX
->
mutable_data
<
T
>
(
context
.
GetPlace
());
const
int
batch_size
=
Y
->
dims
()[
0
];
const
int
class_num
=
Y
->
dims
()[
1
];
Eigen
::
DSizes
<
int
,
1
>
along_class
(
1
);
Eigen
::
DSizes
<
int
,
2
>
batch_by_one
(
batch_size
,
1
);
Eigen
::
DSizes
<
int
,
2
>
one_by_class
(
1
,
class_num
);
auto
*
Y
=
context
.
Input
<
Tensor
>
(
"Y"
);
auto
*
dY
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
auto
*
dX
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
Y_eigen
=
EigenMatrix
<
T
>::
From
(
*
Y
);
auto
dY_eigen
=
EigenMatrix
<
T
>::
From
(
*
dY
);
auto
dX_eigen
=
EigenMatrix
<
T
>::
From
(
*
dX
);
auto
place
=
context
.
GetEigenDevice
<
Place
>
();
// allocate memory on device.
dX
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
dot
=
(
Y_eigen
*
dY_eigen
)
.
sum
(
along_class
)
.
eval
()
.
reshape
(
batch_by_one
)
.
broadcast
(
one_by_class
);
dX_eigen
.
device
(
place
)
=
(
dY_eigen
-
dot
)
*
Y_eigen
;
math
::
SoftmaxGradFunctor
<
Place
,
T
>
()(
context
.
device_context
(),
Y
,
dY
,
dX
);
}
};
...
...
python/paddle/v2/framework/tests/test_sequence_softmax_op.py
0 → 100644
浏览文件 @
a2657fea
import
unittest
import
numpy
as
np
from
op_test
import
OpTest
def
stable_softmax
(
x
):
"""Compute the softmax of vector x in a numerically stable way."""
shiftx
=
x
-
np
.
max
(
x
).
clip
(
-
64.
)
exps
=
np
.
exp
(
shiftx
)
return
exps
/
np
.
sum
(
exps
)
class
TestSequenceSoftmaxOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"sequence_softmax"
x
=
np
.
random
.
uniform
(
0.1
,
1
,
(
11
,
1
)).
astype
(
"float32"
)
lod
=
[[
0
,
4
,
5
,
8
,
11
]]
out
=
np
.
zeros
((
11
,
1
)).
astype
(
"float32"
)
for
i
in
range
(
4
):
sub_x
=
x
[
lod
[
0
][
i
]:
lod
[
0
][
i
+
1
],
:]
sub_x
=
sub_x
.
reshape
(
1
,
lod
[
0
][
i
+
1
]
-
lod
[
0
][
i
])
sub_out
=
stable_softmax
(
sub_x
)
out
[
lod
[
0
][
i
]:
lod
[
0
][
i
+
1
],
:]
=
sub_out
.
reshape
(
lod
[
0
][
i
+
1
]
-
lod
[
0
][
i
],
1
)
self
.
inputs
=
{
"X"
:
(
x
,
lod
)}
self
.
outputs
=
{
"Out"
:
out
}
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
self
.
check_grad
([
"X"
],
"Out"
,
max_relative_error
=
0.01
)
if
__name__
==
"__main__"
:
unittest
.
main
()
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