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体验新版 GitCode,发现更多精彩内容 >>
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8560ce69
编写于
1月 11, 2017
作者:
X
xutianbing
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Daoyuan's comments about SequenceArg.
上级
9edfd200
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
151 addition
and
47 deletion
+151
-47
paddle/function/ContextProjectionOp.cpp
paddle/function/ContextProjectionOp.cpp
+134
-29
paddle/function/ContextProjectionOpTest.cpp
paddle/function/ContextProjectionOpTest.cpp
+10
-10
paddle/gserver/layers/ContextProjection.cpp
paddle/gserver/layers/ContextProjection.cpp
+7
-8
未找到文件。
paddle/function/ContextProjectionOp.cpp
浏览文件 @
8560ce69
...
...
@@ -74,7 +74,7 @@ void ContextProjectionForward<DEVICE_TYPE_CPU>(CpuMatrix& out_mat,
/**
* Paddle Function for Context Projection Forward.
* Calculate the
value for the output layer with
context projection.
* Calculate the
output sequence after
context projection.
*
* What is Context Projection?
* For example, assumed input (x) has 4 words and the dimension of each word
...
...
@@ -92,10 +92,12 @@ void ContextProjectionForward<DEVICE_TYPE_CPU>(CpuMatrix& out_mat,
* c1, c2, d1, d2, 0, 0]
* @endcode
*
* \param outputs[0] output value.
* \param inputs[0] input value.
* \param inputs[1] input weight.
* \param inputs[2] input sequence.
* \param outputs[0].matrix output value, n * (d * l)
* \param outputs[0].vector input sequence, n * 1
* \param inputs[0].matrix input value, n * d
* \param inputs[0].vector input sequence, n * 1
* \param inputs[1].matrix input weight, pad * d
* \param inputs[1].vector input sequence, n * 1
*/
template
<
DeviceType
Device
>
class
ContextProjectionForwardFunc
:
public
FunctionBase
{
...
...
@@ -107,28 +109,40 @@ public:
}
void
calc
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
override
{
CHECK
_EQ
((
size_t
)
3
,
inputs
.
size
());
CHECK
(
1
==
inputs
.
size
()
||
2
==
inputs
.
size
());
CHECK_EQ
((
size_t
)
1
,
outputs
.
size
());
CHECK
(
outputs
[
0
].
data
()
&&
inputs
[
0
].
data
()
&&
inputs
[
2
].
data
());
CHECK_EQ
(
outputs
[
0
].
shape
().
ndims
(),
(
size_t
)
2
);
CHECK_EQ
(
inputs
[
0
].
shape
().
ndims
(),
(
size_t
)
2
);
CHECK_EQ
(
inputs
[
1
].
shape
().
ndims
(),
(
size_t
)
2
);
CHECK_EQ
(
inputs
[
2
].
shape
().
ndims
(),
(
size_t
)
1
);
const
auto
val_seqs
=
dynamic_cast
<
const
SequenceArg
&>
(
inputs
[
0
]);
const
auto
w_seqs
=
inputs
.
size
()
<=
1
?
nullptr
:
dynamic_cast
<
const
SequenceArg
*>
(
&
inputs
[
1
]);
auto
out_seqs
=
dynamic_cast
<
const
SequenceArg
&>
(
outputs
[
0
]);
CHECK
(
out_seqs
.
data
()
&&
val_seqs
.
data
()
&&
val_seqs
.
getSequenceIds
().
data
());
CHECK_EQ
(
out_seqs
.
shape
().
ndims
(),
(
size_t
)
2
);
CHECK_EQ
(
val_seqs
.
shape
().
ndims
(),
(
size_t
)
2
);
CHECK_EQ
(
val_seqs
.
getSequenceIds
().
shape
().
ndims
(),
(
size_t
)
1
);
if
(
w_seqs
)
{
CHECK_EQ
(
w_seqs
->
shape
().
ndims
(),
(
size_t
)
2
);
CHECK_EQ
(
w_seqs
->
getSequenceIds
().
shape
().
ndims
(),
(
size_t
)
1
);
}
/// dim of output = dim of input * context_length
CHECK_EQ
(
outputs
[
0
].
shape
()[
1
],
inputs
[
0
].
shape
()[
1
]
*
context_length_
);
/// dim of input == dim of weight
CHECK_EQ
(
inputs
[
0
].
shape
()[
1
],
inputs
[
1
].
shape
()[
1
]);
CHECK_EQ
(
out_seqs
.
shape
()[
1
],
val_seqs
.
shape
()[
1
]
*
context_length_
);
/// input and output has the same batch_size
CHECK_EQ
(
inputs
[
0
].
shape
()[
0
],
outputs
[
0
].
shape
()[
0
]);
CHECK_EQ
(
val_seqs
.
shape
()[
0
],
out_seqs
.
shape
()[
0
]);
/// dim of input == dim of weight
if
(
w_seqs
)
{
CHECK_EQ
(
val_seqs
.
shape
()[
1
],
w_seqs
->
shape
()[
1
]);
}
CHECK_EQ
(
out
puts
[
0
]
.
getArgType
(),
ADD_TO
);
auto
out_mat
=
out
puts
[
0
]
.
matrix
<
Device
>
();
const
auto
in_mat
=
inputs
[
0
]
.
matrix
<
Device
>
();
CHECK_EQ
(
out
_seqs
.
getArgType
(),
ADD_TO
);
auto
out_mat
=
out
_seqs
.
matrix
<
Device
>
();
const
auto
in_mat
=
val_seqs
.
matrix
<
Device
>
();
const
auto
w_mat
=
!
inputs
[
1
].
data
()
?
typename
Tensor
<
real
,
Device
>::
Matrix
(
nullptr
,
0
,
0
)
:
inputs
[
1
].
matrix
<
Device
>
(
);
const
auto
seq_vec
=
inputs
[
2
]
.
vector
<
int
,
Device
>
();
w_seqs
?
w_seqs
->
matrix
<
Device
>
(
)
:
typename
Tensor
<
real
,
Device
>::
Matrix
(
nullptr
,
0
,
0
);
const
auto
seq_vec
=
val_seqs
.
getSequenceIds
()
.
vector
<
int
,
Device
>
();
ContextProjectionForward
<
Device
>
(
out_mat
,
in_mat
,
w_mat
,
...
...
@@ -227,25 +241,25 @@ public:
CHECK_EQ
((
size_t
)
1
,
inputs
.
size
());
CHECK_EQ
((
size_t
)
2
,
outputs
.
size
());
const
auto
seq
A
rg
=
dynamic_cast
<
const
SequenceArg
&>
(
inputs
[
0
]);
CHECK
(
seq
A
rg
.
data
()
&&
inputs
[
0
].
data
());
CHECK_EQ
(
seq
A
rg
.
shape
().
ndims
(),
(
size_t
)
2
);
CHECK_EQ
(
seq
A
rg
.
getSequenceIds
().
shape
().
ndims
(),
(
size_t
)
1
);
const
auto
seq
_a
rg
=
dynamic_cast
<
const
SequenceArg
&>
(
inputs
[
0
]);
CHECK
(
seq
_a
rg
.
data
()
&&
inputs
[
0
].
data
());
CHECK_EQ
(
seq
_a
rg
.
shape
().
ndims
(),
(
size_t
)
2
);
CHECK_EQ
(
seq
_a
rg
.
getSequenceIds
().
shape
().
ndims
(),
(
size_t
)
1
);
CHECK_EQ
(
outputs
[
0
].
shape
().
ndims
(),
(
size_t
)
2
);
CHECK_EQ
(
outputs
[
1
].
shape
().
ndims
(),
(
size_t
)
2
);
/// dim of input grad == dim of weight
CHECK_EQ
(
outputs
[
0
].
shape
()[
1
],
outputs
[
1
].
shape
()[
1
]);
/// input and output grad has the same batch_size
CHECK_EQ
(
outputs
[
0
].
shape
()[
0
],
seq
A
rg
.
shape
()[
0
]);
CHECK_EQ
(
outputs
[
0
].
shape
()[
0
],
seq
_a
rg
.
shape
()[
0
]);
/// dim of output val = dim of input grad * context_length
CHECK_EQ
(
seq
A
rg
.
shape
()[
1
],
outputs
[
0
].
shape
()[
1
]
*
context_length_
);
CHECK_EQ
(
seq
_a
rg
.
shape
()[
1
],
outputs
[
0
].
shape
()[
1
]
*
context_length_
);
CHECK_EQ
(
outputs
[
0
].
getArgType
(),
ADD_TO
);
CHECK_EQ
(
outputs
[
1
].
getArgType
(),
ADD_TO
);
const
auto
seq_vec
=
seq
A
rg
.
getSequenceIds
().
vector
<
int
,
Device
>
();
const
auto
out_grad_mat
=
seq
A
rg
.
matrix
<
Device
>
();
const
auto
seq_vec
=
seq
_a
rg
.
getSequenceIds
().
vector
<
int
,
Device
>
();
const
auto
out_grad_mat
=
seq
_a
rg
.
matrix
<
Device
>
();
auto
in_grad_mat
=
!
outputs
[
0
].
data
()
?
typename
Tensor
<
real
,
Device
>::
Matrix
(
nullptr
,
0
,
0
)
...
...
@@ -272,6 +286,91 @@ private:
size_t
total_pad_
;
};
/**
* \param inputs[0].matrix input grad, n*d
* \param inputs[0].vector input sequence, n*1
* \param outputs[0] output grad, n*(d*l)
*/
template
<
DeviceType
Device
>
class
ContextProjectionBackwardDataFunc
:
public
FunctionBase
{
public:
void
init
(
const
FuncConfig
&
config
)
override
{
context_length_
=
config
.
get
<
size_t
>
(
"context_length"
);
context_start_
=
config
.
get
<
int
>
(
"context_start"
);
}
void
calc
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
override
{
CHECK_EQ
(
1
,
static_cast
<
int
>
(
inputs
.
size
()));
CHECK_EQ
(
1
,
static_cast
<
int
>
(
outputs
.
size
()));
const
auto
in_seqs
=
dynamic_cast
<
const
SequenceArg
&>
(
inputs
[
0
]);
CHECK
(
in_seqs
.
data
()
&&
outputs
[
0
].
data
()
&&
in_seqs
.
getSequenceIds
().
data
());
CHECK_EQ
(
static_cast
<
int
>
(
outputs
[
0
].
shape
().
ndims
()),
2
);
CHECK_EQ
(
static_cast
<
int
>
(
in_seqs
.
shape
().
ndims
()),
2
);
CHECK_EQ
(
static_cast
<
int
>
(
in_seqs
.
getSequenceIds
().
shape
().
ndims
()),
1
);
CHECK_EQ
(
outputs
[
0
].
shape
().
ndims
(),
in_seqs
.
shape
().
ndims
()
*
context_length_
);
/// input and output has the same batch_size
CHECK_EQ
(
in_seqs
.
shape
()[
0
],
outputs
[
0
].
shape
()[
0
]);
const
auto
out_grad_mat
=
outputs
[
0
].
matrix
<
Device
>
();
auto
in_grad_mat
=
in_seqs
.
matrix
<
Device
>
();
const
auto
seq_vec
=
in_seqs
.
getSequenceIds
().
vector
<
int
,
Device
>
();
ContextProjectionBackwardData
<
Device
>
(
out_grad_mat
,
in_grad_mat
,
seq_vec
,
context_length_
,
context_start_
);
}
private:
size_t
context_length_
;
int
context_start_
;
};
/**
* \param inputs[0].matrix weight grad, pad * d
* \param inputs[0].vecotr input sequence, n * 1
* \param outputs[0] output grad, n * (d * l)
*/
template
<
DeviceType
Device
>
class
ContextProjectionBackwardWeightFunc
:
public
FunctionBase
{
public:
void
init
(
const
FuncConfig
&
config
)
override
{
context_length_
=
config
.
get
<
size_t
>
(
"context_length"
);
context_start_
=
config
.
get
<
int
>
(
"context_start"
);
begin_pad_
=
config
.
get
<
size_t
>
(
"begin_pad"
);
total_pad_
=
config
.
get
<
size_t
>
(
"total_pad"
);
}
void
calc
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
override
{
CHECK_EQ
(
1
,
static_cast
<
int
>
(
inputs
.
size
()));
CHECK_EQ
(
1
,
static_cast
<
int
>
(
outputs
.
size
()));
const
auto
in_seqs
=
dynamic_cast
<
const
SequenceArg
&>
(
inputs
[
0
]);
CHECK
(
in_seqs
.
data
()
&&
in_seqs
.
getSequenceIds
().
data
()
&&
outputs
[
0
].
data
());
CHECK_EQ
(
static_cast
<
int
>
(
outputs
[
0
].
shape
().
ndims
()),
2
);
CHECK_EQ
(
static_cast
<
int
>
(
in_seqs
.
shape
().
ndims
()),
2
);
CHECK_EQ
(
static_cast
<
int
>
(
in_seqs
.
getSequenceIds
().
shape
().
ndims
()),
1
);
CHECK_EQ
(
in_seqs
.
shape
()[
0
],
outputs
[
0
].
shape
()[
0
]);
CHECK_EQ
(
outputs
[
0
].
shape
()[
1
],
in_seqs
.
shape
()[
1
]
*
context_length_
);
const
auto
out_grad_mat
=
outputs
[
0
].
matrix
<
Device
>
();
auto
w_grad_mat
=
inputs
[
0
].
matrix
<
Device
>
();
const
auto
seq_vec
=
in_seqs
.
getSequenceIds
().
vector
<
int
,
Device
>
();
ContextProjectionBackwardWeight
<
Device
>
(
out_grad_mat
,
w_grad_mat
,
seq_vec
,
context_length_
,
context_start_
,
total_pad_
,
begin_pad_
);
}
private:
size_t
context_length_
;
int
context_start_
;
size_t
begin_pad_
;
size_t
total_pad_
;
};
REGISTER_TYPED_FUNC
(
ContextProjectionForward
,
CPU
,
ContextProjectionForwardFunc
);
...
...
@@ -285,5 +384,11 @@ REGISTER_TYPED_FUNC(ContextProjectionForward,
REGISTER_TYPED_FUNC
(
ContextProjectionBackward
,
GPU
,
ContextProjectionBackwardFunc
);
REGISTER_TYPED_FUNC
(
ContextProjectionBackwardData
,
GPU
,
ContextProjectionBackwardDataFunc
);
REGISTER_TYPED_FUNC
(
ContextProjectionBackwardWeight
,
GPU
,
ContextProjectionBackwardWeightFunc
);
#endif
}
// namespace paddle
paddle/function/ContextProjectionOpTest.cpp
浏览文件 @
8560ce69
...
...
@@ -58,21 +58,21 @@ void testMatrixProjectionForward(int context_start,
BufferArgs
cpu_inputs
;
BufferArgs
cpu_outputs
;
cpu_inputs
.
addArg
(
cpu_in
);
cpu_inputs
.
addArg
(
cpu_weight
?
*
cpu_weight
:
CpuMatrix
(
nullptr
,
0
,
input_dim
)
);
cpu_inputs
.
addArg
(
*
cpu_seq
);
cpu_outputs
.
addArg
(
cpu_out
,
ADD_TO
);
cpu_inputs
.
addArg
(
cpu_in
,
*
cpu_seq
);
if
(
cpu_weight
)
{
cpu_inputs
.
addArg
(
*
cpu_weight
,
*
cpu_seq
);
}
cpu_outputs
.
addArg
(
cpu_out
,
*
cpu_seq
,
ADD_TO
);
compare
.
getCpuFunction
()
->
calc
(
cpu_inputs
,
cpu_outputs
);
BufferArgs
gpu_inputs
;
BufferArgs
gpu_outputs
;
gpu_inputs
.
addArg
(
gpu_in
);
gpu_inputs
.
addArg
(
gpu_weight
?
*
gpu_weight
:
GpuMatrix
(
nullptr
,
0
,
input_dim
)
);
gpu_inputs
.
addArg
(
*
gpu_seq
);
gpu_outputs
.
addArg
(
gpu_out
,
ADD_TO
);
gpu_inputs
.
addArg
(
gpu_in
,
*
gpu_seq
);
if
(
gpu_weight
)
{
gpu_inputs
.
addArg
(
*
gpu_weight
,
*
gpu_seq
);
}
gpu_outputs
.
addArg
(
gpu_out
,
*
gpu_seq
,
ADD_TO
);
compare
.
getGpuFunction
()
->
calc
(
gpu_inputs
,
gpu_outputs
);
...
...
paddle/gserver/layers/ContextProjection.cpp
浏览文件 @
8560ce69
...
...
@@ -118,16 +118,15 @@ void ContextProjection::forward() {
/// first use state_, otherwise use weight_(padding false === w nullptr)
auto
w_ptr
=
state_
?
state_
.
get
()
:
is_padding
?
weight_
->
getW
().
get
()
:
nullptr
;
auto
start_pos
=
in_
->
sequenceStartPositions
;
const
auto
start_pos
=
in_
->
sequenceStartPositions
->
getVector
(
useGpu_
);
BufferArgs
inputs
;
BufferArgs
outputs
;
inputs
.
addArg
(
*
in_
->
value
);
i
nputs
.
addArg
(
CpuMatrix
(
w_ptr
?
w_ptr
->
getData
()
:
nullptr
,
w_ptr
?
w_ptr
->
getHeight
()
:
0
,
input_dim
)
);
inputs
.
addArg
(
*
in_
->
sequenceStartPositions
->
getVector
(
useGpu_
));
outputs
.
addArg
(
*
out_
->
value
,
ADD_TO
);
inputs
.
addArg
(
*
in_
->
value
,
*
start_pos
);
i
f
(
w_ptr
)
{
inputs
.
addArg
(
CpuMatrix
(
w_ptr
->
getData
(),
w_ptr
->
getHeight
(),
input_dim
)
,
*
start_pos
);
}
outputs
.
addArg
(
*
out_
->
value
,
*
start_pos
,
ADD_TO
);
forward_
[
0
]
->
calc
(
inputs
,
outputs
);
if
(
state_
&&
config_
.
context_start
()
<
0
)
{
...
...
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