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体验新版 GitCode,发现更多精彩内容 >>
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d211b51b
编写于
10月 10, 2017
作者:
Y
Yancey1989
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0028459b
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3
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Showing
3 changed file
with
67 addition
and
50 deletion
+67
-50
paddle/operators/sequence_concat_op.cc
paddle/operators/sequence_concat_op.cc
+29
-20
paddle/operators/sequence_concat_op.h
paddle/operators/sequence_concat_op.h
+8
-20
python/paddle/v2/framework/tests/test_seq_concat_op.py
python/paddle/v2/framework/tests/test_seq_concat_op.py
+30
-10
未找到文件。
paddle/operators/sequence_concat_op.cc
浏览文件 @
d211b51b
...
...
@@ -48,11 +48,11 @@ class SequenceConcatOpMaker : public framework::OpProtoAndCheckerMaker {
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"
The input Multip LoDTensors, which are variable-length
"
"sequence or nested sequence."
)
"
(A vector of LoDTensor), the input is a vector of LoDTensor,
"
"
each of which is a variable-length
sequence or nested sequence."
)
.
AsDuplicable
();
AddOutput
(
"Out"
,
"
A LoDTensor
, the variable-length output of "
"
(A LoDTensor)
, the variable-length output of "
"sequence_concat Op."
);
AddAttr
<
int
>
(
"axis"
,
"(int, default 0)"
...
...
@@ -61,27 +61,36 @@ class SequenceConcatOpMaker : public framework::OpProtoAndCheckerMaker {
.
SetDefault
(
0
);
AddAttr
<
int
>
(
"level"
,
"(int, default 0)"
"The level which the inputs will be joined with."
"If level is 0, the inputs will be joined with "
"nested sequences."
"If level is 1, the inputs will be joined with sequences."
)
"The level at which the inputs will be joined."
"If the level is 0, the inputs will be joined at the nested "
"sequence level."
"If the level is 1, the inputs will be joined at the "
"sequence level."
)
.
SetDefault
(
0
);
AddComment
(
R"DOC(
The sequence_concat operator concatenates multiple LoDTensors.
It only supports sequence
s ( LoD Tensor with level=
1)
or
nested sequences (LoD tensor with level=0) as its inputs
.
It only supports sequence
(LoD Tensor with level number is
1)
or
a nested sequence (LoD tensor with level number is 2) as its input
.
- Case1:
If the axis is 1, level is 1, the LoD of Inputs are the same,
LoD(x0) = {{0,2,4},{0,1,2,3,4}}; Dims(x0) = (2,3,4)
LoD(x1) = {{0,2,4},{0,1,2,3,4}}; Dims(x1) = (2,4,4)
LoD(Out) = {{0,2,4},{0,1,2,3,4}}; Dims(Out) = (2,7,4)
If the axis is other than 0(here, axis is 1 and level is 1),
each input should have the same LoD information and the LoD
information of the output keeps the same as the input.
LoD(x0) = {{0,2,4}, {0,1,2,3,4}}; Dims(x0) = (4,3,4)
LoD(x1) = {{0,2,4}, {0,1,2,3,4}}; Dims(x1) = (4,4,4)
LoD(Out) = {{0,2,4}, {0,1,2,3,4}}; Dims(Out) = (4,7,4)
- Case2:
If the axis is 0, level is 1, the LoD of inputs are different,
LoD(x0) = {{0,2,4}, {0,1,2,3,4}}; Dims(x0) = (2,3,4)
LoD(x1) = {{0,3,5}, {0,1,3,4,5}}; Dims(x1) = (3,3,4)
LoD(Out) = {{0,5,9}, {0,1,2,4,5,6,7,8,9}}; Dims(Out) = (5,3,4)
NOTE: The level of all the inputs should be the same.
If the axis is 0(here, leve is 0), the inputs are concatenated along
time steps, the LoD information of the output need to re-compute.
LoD(x0) = {{0,2,4}, {0,1,2,3,4}}; Dims(x0) = (4,3,4)
LoD(x1) = {{0,3,5}, {0,1,2,3,5}}; Dims(x1) = (5,3,4)
LoD(Out) = {{0,5,9}, {0,1,2,3,4,5,6,7,9}}; Dims(Out) = (9,3,4)
- Case3:
If the axis is 0(here, level is 1).
LoD(x0) = {{0,2,4}, {0,1,2,3,4}}; Dims(x0) = (4,3,4)
LoD(x1) = {{0,3,5}, {0,1,3,4,5}}; Dims(x1) = (5,3,4)
LoD(Out) = {{0,5,9}, {0,2,5,7,9}}; Dims(Out) = (9,3,4)
NOTE: The levels of all the inputs should be the same.
)DOC"
);
}
};
...
...
@@ -95,7 +104,7 @@ class SequenceConcatGradOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"The gradient of Out should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutputs
(
framework
::
GradVarName
(
"X"
)),
"The gradient of X should not be
empty
."
);
"The gradient of X should not be
null
."
);
ctx
->
SetOutputsDim
(
framework
::
GradVarName
(
"X"
),
ctx
->
GetInputsDim
(
"X"
));
}
};
...
...
paddle/operators/sequence_concat_op.h
浏览文件 @
d211b51b
...
...
@@ -23,35 +23,22 @@ using Tensor = framework::Tensor;
using
LoDTensor
=
framework
::
LoDTensor
;
using
LoD
=
framework
::
LoD
;
// Concat LoD, the initialized LoD of Output is lod(x0),
// if axis is not 0, the LoD(Out) will be the same as Inputs, if axis is 0:
// Case1:
// There is one level, the Output LoD will be modified:
// LoD(x0) = {{0,2,4}}
// LoD(x1) = {{0,1,5}}
// LoD(Out) = {{0,3,9}}
// Case2:
// There is two level, and concat level is 1,
// the Output LoD will be modified as followed:
// LoD(x0) = {{0,2,4}, {0,1,2,3,4}}
// LoD(x1) = {{0,3,5}, {0,1,3,4,5}}
// LoD(Out) = {{0,5,9}, {0,1,2,4,5,6,7,8,9}}
template
<
typename
T
>
LoD
concatLoD
(
const
std
::
vector
<
const
T
*>
ins
,
const
size_t
axis
,
const
size_t
level
)
{
auto
out_lod
=
ins
[
0
]
->
lod
();
const
size_t
n
=
ins
.
size
();
if
(
axis
==
0UL
)
{
if
(
level
==
0
)
{
if
(
level
==
0
UL
)
{
for
(
size_t
i
=
1
;
i
<
n
;
++
i
)
{
for
(
size_t
j
=
0
;
j
<
ins
[
i
]
->
lod
()[
0
].
size
();
++
j
)
{
out_lod
[
0
][
j
]
+=
ins
[
i
]
->
lod
()[
0
][
j
];
}
}
}
else
if
(
level
==
1
)
{
}
else
if
(
level
==
1
UL
)
{
PADDLE_ENFORCE_EQ
(
ins
[
0
]
->
NumLevels
(),
2UL
,
"If the level is 1, all of the inputs "
"should be the
the
nested sequence."
);
"should be the nested sequence."
);
for
(
size_t
i
=
1
;
i
<
n
;
++
i
)
{
for
(
size_t
j
=
0
;
j
<
ins
[
i
]
->
lod
()[
0
].
size
();
++
j
)
{
out_lod
[
0
].
push_back
(
ins
[
i
]
->
lod
()[
0
][
j
]);
...
...
@@ -80,16 +67,17 @@ class SequenceConcatOpKernel : public framework::OpKernel<T> {
"The level number of all the input LoDTensors "
"should be the same."
);
PADDLE_ENFORCE_EQ
(
ins
[
0
]
->
dims
().
size
(),
ins
[
i
]
->
dims
().
size
(),
"The dimension
s
size of all the input LoDTensors "
"The dimension size of all the input LoDTensors "
"should be the same."
);
const
size_t
dims_size
=
ins
[
i
]
->
dims
().
size
();
for
(
size_t
j
=
0
;
j
<
dims_size
;
++
j
)
{
if
(
j
==
axis
)
continue
;
PADDLE_ENFORCE_EQ
(
ins
[
0
]
->
dims
()[
j
],
ins
[
i
]
->
dims
()[
j
],
"The dimensions of all the input LoDTensors "
"except for the specify axis should be "
"matched exactly."
);
"Except for the dimension of the specified "
"axis along which all the inputs are concatenated, "
"dimensions of all the other axises of the input "
"LoDTensors should be the same."
);
}
}
...
...
python/paddle/v2/framework/tests/test_seq_concat_op.py
浏览文件 @
d211b51b
...
...
@@ -6,16 +6,16 @@ from op_test import OpTest
class
TestConcatOp
(
OpTest
):
def
set_data
(
self
):
# two level, batch size is 3
x0
=
np
.
random
.
random
((
11
,
6
,
3
)).
astype
(
'float32'
)
lod0
=
[[
0
,
2
,
5
,
11
],
[
0
,
1
,
2
,
5
,
7
,
11
]]
x1
=
np
.
random
.
random
((
11
,
8
,
3
)).
astype
(
'float32'
)
lod1
=
[[
0
,
2
,
5
,
11
],
[
0
,
1
,
2
,
5
,
7
,
11
]]
x0
=
np
.
random
.
random
((
4
,
6
,
3
)).
astype
(
'float32'
)
lod0
=
[[
0
,
2
,
4
],
[
0
,
1
,
2
,
3
,
4
]]
x1
=
np
.
random
.
random
((
4
,
8
,
3
)).
astype
(
'float32'
)
lod1
=
[[
0
,
2
,
4
],
[
0
,
1
,
2
,
3
,
4
]]
axis
=
1
level
=
1
self
.
inputs
=
{
'X'
:
[(
'x0'
,
(
x0
,
lod0
)),
(
'x1'
,
(
x1
,
lod1
))]}
self
.
attrs
=
{
'axis'
:
axis
,
'level'
:
level
}
outs
=
[]
for
i
in
range
(
5
):
for
i
in
range
(
4
):
sub_x0
=
x0
[
lod0
[
level
][
i
]:
lod0
[
level
][
i
+
1
],
:]
sub_x1
=
x1
[
lod1
[
level
][
i
]:
lod1
[
level
][
i
+
1
],
:]
outs
.
append
(
np
.
concatenate
((
sub_x0
,
sub_x1
),
axis
=
axis
))
...
...
@@ -36,16 +36,36 @@ class TestConcatOp(OpTest):
class
TestConcatOpDiffLod
(
TestConcatOp
):
def
set_data
(
self
):
# two level, batch size is 3
x0
=
np
.
random
.
random
((
12
,
6
,
3
)).
astype
(
'float32'
)
lod0
=
[[
0
,
3
,
9
,
12
],
[
0
,
2
,
3
,
5
,
9
,
12
]]
x1
=
np
.
random
.
random
((
11
,
6
,
3
)).
astype
(
'float32'
)
lod1
=
[[
0
,
2
,
5
,
11
],
[
0
,
1
,
2
,
5
,
7
,
11
]]
x0
=
np
.
random
.
random
((
4
,
6
,
3
)).
astype
(
'float32'
)
lod0
=
[[
0
,
2
,
4
],
[
0
,
1
,
2
,
3
,
4
]]
x1
=
np
.
random
.
random
((
5
,
6
,
3
)).
astype
(
'float32'
)
lod1
=
[[
0
,
3
,
5
],
[
0
,
1
,
2
,
3
,
5
]]
axis
=
0
level
=
1
self
.
inputs
=
{
'X'
:
[(
'x0'
,
(
x0
,
lod0
)),
(
'x1'
,
(
x1
,
lod1
))]}
self
.
attrs
=
{
'axis'
:
axis
,
'level'
:
level
}
outs
=
[]
for
i
in
range
(
5
):
for
i
in
range
(
4
):
sub_x0
=
x0
[
lod0
[
level
][
i
]:
lod0
[
level
][
i
+
1
],
:]
sub_x1
=
x1
[
lod1
[
level
][
i
]:
lod1
[
level
][
i
+
1
],
:]
outs
.
append
(
np
.
concatenate
((
sub_x0
,
sub_x1
),
axis
=
axis
))
self
.
outputs
=
{
'Out'
:
np
.
concatenate
(
outs
,
axis
=
0
)}
class
TestConcatOpLevelZero
(
TestConcatOp
):
def
set_data
(
self
):
# two level, batch size is 3
x0
=
np
.
random
.
random
((
4
,
3
,
4
)).
astype
(
'float32'
)
lod0
=
[[
0
,
2
,
4
],
[
0
,
1
,
2
,
3
,
4
]]
x1
=
np
.
random
.
random
((
5
,
3
,
4
)).
astype
(
'float32'
)
lod1
=
[[
0
,
3
,
5
],
[
0
,
1
,
3
,
4
,
5
]]
axis
=
0
level
=
0
self
.
inputs
=
{
'X'
:
[(
'x0'
,
(
x0
,
lod0
)),
(
'x1'
,
(
x1
,
lod1
))]}
self
.
attrs
=
{
'axis'
:
axis
,
'level'
:
level
}
outs
=
[]
for
i
in
range
(
2
):
sub_x0
=
x0
[
lod0
[
level
][
i
]:
lod0
[
level
][
i
+
1
],
:]
sub_x1
=
x1
[
lod1
[
level
][
i
]:
lod1
[
level
][
i
+
1
],
:]
outs
.
append
(
np
.
concatenate
((
sub_x0
,
sub_x1
),
axis
=
axis
))
...
...
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