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8925295a
编写于
8月 01, 2017
作者:
D
dangqingqing
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
follow comments.
上级
b89d15a3
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
69 addition
and
67 deletion
+69
-67
paddle/operators/recurrent_network_op.cc
paddle/operators/recurrent_network_op.cc
+54
-57
paddle/operators/recurrent_network_op.h
paddle/operators/recurrent_network_op.h
+6
-5
paddle/operators/recurrent_network_op_test.cc
paddle/operators/recurrent_network_op_test.cc
+9
-5
未找到文件。
paddle/operators/recurrent_network_op.cc
浏览文件 @
8925295a
...
...
@@ -30,11 +30,14 @@ namespace rnn {
void
SegmentInputs
(
std
::
vector
<
std
::
shared_ptr
<
Scope
>>&
step_scopes
,
const
std
::
vector
<
Link
>&
inlinks
,
const
size_t
seq_len
,
bool
infer_shape
)
{
bool
infer_shape
_mode
)
{
PADDLE_ENFORCE
(
!
inlinks
.
empty
(),
"no in links are provided."
);
for
(
size_t
i
=
0
;
i
<
inlinks
.
size
();
++
i
)
{
Tensor
*
input
=
step_scopes
[
0
]
->
GetVariable
(
inlinks
[
i
].
external
)
->
GetMutable
<
Tensor
>
();
auto
input_var
=
step_scopes
[
0
]
->
GetVariable
(
inlinks
[
i
].
external
);
PADDLE_ENFORCE
(
input_var
!=
nullptr
,
"input link [%s] is not in scope."
,
inlinks
[
i
].
external
);
Tensor
*
input
=
input_var
->
GetMutable
<
Tensor
>
();
DDim
dims
=
input
->
dims
();
PADDLE_ENFORCE
(
static_cast
<
size_t
>
(
dims
[
0
])
==
seq_len
,
"all the inlinks must have same length"
);
...
...
@@ -43,7 +46,7 @@ void SegmentInputs(std::vector<std::shared_ptr<Scope>>& step_scopes,
Tensor
*
step_input
=
step_scopes
[
j
]
->
CreateVariable
(
inlinks
[
i
].
internal
)
->
GetMutable
<
Tensor
>
();
if
(
!
infer_shape
)
{
if
(
!
infer_shape
_mode
)
{
*
step_input
=
input
->
Slice
<
float
>
(
j
,
j
+
1
);
}
step_input
->
Resize
(
step_dims
);
...
...
@@ -54,12 +57,14 @@ void SegmentInputs(std::vector<std::shared_ptr<Scope>>& step_scopes,
void
ConcatOutputs
(
std
::
vector
<
std
::
shared_ptr
<
Scope
>>&
step_scopes
,
const
std
::
vector
<
Link
>&
outlinks
,
const
size_t
seq_len
,
bool
infer_shape
)
{
bool
infer_shape
_mode
)
{
for
(
size_t
i
=
0
;
i
<
outlinks
.
size
();
i
++
)
{
PADDLE_ENFORCE
(
step_scopes
[
0
]
->
HasVariable
(
outlinks
[
i
].
external
),
"output link [%s] is not in scope."
,
outlinks
[
i
].
external
);
Tensor
*
output
=
step_scopes
[
0
]
->
GetVariable
(
outlinks
[
i
].
external
)
->
GetMutable
<
Tensor
>
();
if
(
infer_shape
)
{
if
(
infer_shape_mode
)
{
DDim
step_dims
=
step_scopes
[
0
]
->
GetVariable
(
outlinks
[
i
].
internal
)
->
GetMutable
<
Tensor
>
()
...
...
@@ -69,16 +74,15 @@ void ConcatOutputs(std::vector<std::shared_ptr<Scope>>& step_scopes,
output
->
Resize
(
make_ddim
(
dims_vec
));
}
else
{
output
->
mutable_data
<
float
>
(
platform
::
CPUPlace
());
}
for
(
size_t
j
=
0
;
j
<
seq_len
;
j
++
)
{
Tensor
*
step_output
=
step_scopes
[
j
]
->
GetVariable
(
outlinks
[
i
].
internal
)
->
GetMutable
<
Tensor
>
();
// TODO(luotao02) data type and platform::DeviceContext() should set
// correctly
(
output
->
Slice
<
float
>
(
j
,
j
+
1
))
.
CopyFrom
<
float
>
(
*
step_output
,
platform
::
CPUPlace
());
for
(
size_t
j
=
0
;
j
<
seq_len
;
j
++
)
{
Tensor
*
step_output
=
step_scopes
[
j
]
->
GetVariable
(
outlinks
[
i
].
internal
)
->
GetMutable
<
Tensor
>
();
// TODO(luotao02) data type and platform::DeviceContext() should set
// correctly
(
output
->
Slice
<
float
>
(
j
,
j
+
1
))
.
CopyFrom
<
float
>
(
*
step_output
,
platform
::
CPUPlace
());
}
}
}
}
...
...
@@ -87,7 +91,7 @@ void LinkMemories(std::vector<std::shared_ptr<Scope>>& scopes,
const
std
::
vector
<
rnn
::
MemoryAttr
>&
memories
,
const
size_t
step_id
,
const
int
offset
,
bool
infer_shape
)
{
bool
infer_shape
_mode
)
{
PADDLE_ENFORCE
(
step_id
<
scopes
.
size
(),
"step [%d] is out of range of step scopes' size [%d]"
,
step_id
,
...
...
@@ -107,7 +111,7 @@ void LinkMemories(std::vector<std::shared_ptr<Scope>>& scopes,
auto
mem
=
scope
->
GetVariable
(
attr
.
pre_var
)
->
GetMutable
<
Tensor
>
();
// maybe share variable is better?
auto
linked_mem
=
linked_scope
->
GetVariable
(
attr
.
var
)
->
GetMutable
<
Tensor
>
();
if
(
infer_shape
)
{
if
(
infer_shape
_mode
)
{
mem
->
Resize
(
linked_mem
->
dims
());
}
else
{
mem
->
ShareDataWith
<
float
>
(
*
linked_mem
);
...
...
@@ -179,43 +183,39 @@ void RecurrentAlgorithm::InferShape(const std::shared_ptr<Scope>& scope) const {
->
GetMutable
<
Tensor
>
()
->
dims
()[
0
];
CreateScopes
(
scope
);
auto
step_scopes
=
GetStepScopes
(
scope
);
rnn
::
SegmentInputs
(
step_scopes
,
arg_
->
inlinks
,
seq_len_
,
true
);
InitMemories
(
step_scopes
[
0
],
true
);
PADDLE_ENFORCE
(
scope
->
HasVariable
(
arg_
->
step_net
),
"stepnet [%s] is not in scope."
,
arg_
->
step_net
);
rnn
::
SegmentInputs
(
step_scopes
,
arg_
->
inlinks
,
seq_len_
,
true
/*infer_shape_mode*/
);
InitMemories
(
step_scopes
[
0
],
true
/*infer_shape_mode*/
);
Variable
*
net
=
scope
->
GetVariable
(
arg_
->
step_net
);
PADDLE_ENFORCE
(
net
!=
nullptr
,
"failed to get step net"
);
for
(
size_t
i
=
0
;
i
<
seq_len_
;
i
++
)
{
if
(
i
>
0
)
{
rnn
::
LinkMemories
(
step_scopes
,
arg_
->
memories
,
i
,
-
1
,
true
);
rnn
::
LinkMemories
(
step_scopes
,
arg_
->
memories
,
i
,
-
1
,
true
/*infer_shape_mode*/
);
}
net
->
GetMutable
<
NetOp
>
()
->
InferShape
(
step_scopes
[
i
]);
}
rnn
::
ConcatOutputs
(
step_scopes
,
arg_
->
outlinks
,
seq_len_
,
true
);
rnn
::
ConcatOutputs
(
step_scopes
,
arg_
->
outlinks
,
seq_len_
,
true
/*infer_shape_mode*/
);
}
void
RecurrentAlgorithm
::
Run
(
const
std
::
shared_ptr
<
Scope
>&
scope
,
const
platform
::
DeviceContext
&
dev_ctx
)
const
{
auto
step_scopes
=
GetStepScopes
(
scope
);
rnn
::
SegmentInputs
(
step_scopes
,
arg_
->
inlinks
,
seq_len_
,
false
);
InitMemories
(
step_scopes
[
0
],
false
);
rnn
::
SegmentInputs
(
step_scopes
,
arg_
->
inlinks
,
seq_len_
,
false
/*infer_shape_mode*/
);
InitMemories
(
step_scopes
[
0
],
false
/*infer_shape_mode*/
);
Variable
*
net
=
scope
->
GetVariable
(
arg_
->
step_net
);
for
(
size_t
step_id
=
0
;
step_id
<
seq_len_
;
step_id
++
)
{
if
(
step_id
>
0
)
{
rnn
::
LinkMemories
(
step_scopes
,
arg_
->
memories
,
step_id
,
-
1
,
false
);
rnn
::
LinkMemories
(
step_scopes
,
arg_
->
memories
,
step_id
,
-
1
,
false
/*infer_shape_mode*/
);
}
net
->
GetMutable
<
NetOp
>
()
->
Run
(
step_scopes
[
step_id
],
dev_ctx
);
}
rnn
::
ConcatOutputs
(
step_scopes
,
arg_
->
outlinks
,
seq_len_
,
false
);
rnn
::
ConcatOutputs
(
step_scopes
,
arg_
->
outlinks
,
seq_len_
,
false
/*infer_shape_mode*/
);
}
void
RecurrentAlgorithm
::
CreateScopes
(
std
::
shared_ptr
<
Scope
>
scope
)
const
{
...
...
@@ -227,7 +227,6 @@ void RecurrentAlgorithm::CreateScopes(std::shared_ptr<Scope> scope) const {
if
(
seq_len_
>
step_scopes
->
size
())
{
for
(
size_t
i
=
step_scopes
->
size
();
i
<
seq_len_
;
++
i
)
{
std
::
shared_ptr
<
Scope
>
step_scope
=
std
::
make_shared
<
Scope
>
(
scope
);
// Now all variables in scope must be created outside of op.
auto
net_op
=
scope
->
GetVariable
(
arg_
->
step_net
)
->
GetMutable
<
NetOp
>
();
for
(
auto
&
input
:
net_op
->
inputs_
)
{
...
...
@@ -237,14 +236,13 @@ void RecurrentAlgorithm::CreateScopes(std::shared_ptr<Scope> scope) const {
for
(
auto
&
output
:
net_op
->
outputs_
)
{
step_scope
->
CreateVariable
(
output
);
}
step_scopes
->
push_back
(
std
::
make_shared
<
Scope
>
(
step_scope
));
}
}
}
void
RecurrentAlgorithm
::
InitMemories
(
std
::
shared_ptr
<
Scope
>
step_scope
,
bool
infer_shape
)
const
{
bool
infer_shape
_mode
)
const
{
for
(
auto
&
attr
:
arg_
->
memories
)
{
Tensor
*
pre_mem
=
step_scope
->
CreateVariable
(
attr
.
pre_var
)
->
GetMutable
<
Tensor
>
();
...
...
@@ -254,7 +252,7 @@ void RecurrentAlgorithm::InitMemories(std::shared_ptr<Scope> step_scope,
attr
.
boot_var
);
Tensor
*
boot_mem
=
step_scope
->
GetVariable
(
attr
.
boot_var
)
->
GetMutable
<
Tensor
>
();
if
(
infer_shape
)
{
if
(
infer_shape
_mode
)
{
pre_mem
->
Resize
(
boot_mem
->
dims
());
}
else
{
pre_mem
->
ShareDataWith
<
float
>
(
*
boot_mem
);
...
...
@@ -320,23 +318,23 @@ void RecurrentGradientAlgorithm::Run(
const
std
::
shared_ptr
<
Scope
>&
scope
,
const
platform
::
DeviceContext
&
dev_ctx
)
const
{
auto
step_scopes
=
GetStepScopes
(
scope
);
rnn
::
SegmentInputs
(
step_scopes
,
arg_
->
inlinks
,
seq_len_
,
false
);
PADDLE_ENFORCE
(
scope
->
HasVariable
(
arg_
->
step_net
),
"step net is not in scope."
);
rnn
::
SegmentInputs
(
step_scopes
,
arg_
->
inlinks
,
seq_len_
,
false
/*infer_shape_mode*/
);
Variable
*
net
=
scope
->
GetVariable
(
arg_
->
step_net
);
PADDLE_ENFORCE
(
net
!=
nullptr
,
"failed to get step net"
);
for
(
int
step_id
=
seq_len_
-
1
;
step_id
>=
0
;
--
step_id
)
{
if
(
static_cast
<
size_t
>
(
step_id
)
!=
seq_len_
-
1
)
{
rnn
::
LinkMemories
(
step_scopes
,
arg_
->
memories
,
step_id
,
1
,
false
);
rnn
::
LinkMemories
(
step_scopes
,
arg_
->
memories
,
step_id
,
1
,
false
/*infer_shape_mode*/
);
}
net
->
GetMutable
<
NetOp
>
()
->
Run
(
step_scopes
[
step_id
],
dev_ctx
);
}
LinkBootMemoryGradients
(
step_scopes
[
0
],
false
);
rnn
::
ConcatOutputs
(
step_scopes
,
arg_
->
outlinks
,
seq_len_
,
false
);
rnn
::
ConcatOutputs
(
step_scopes
,
arg_
->
outlinks
,
seq_len_
,
false
/*infer_shape_mode*/
);
}
void
RecurrentGradientAlgorithm
::
LinkBootMemoryGradients
(
std
::
shared_ptr
<
Scope
>
step_scope
,
bool
infer_shape
)
const
{
std
::
shared_ptr
<
Scope
>
step_scope
,
bool
infer_shape
_mode
)
const
{
for
(
auto
&
attr
:
arg_
->
memories
)
{
Tensor
*
mem_grad
=
step_scope
->
CreateVariable
(
attr
.
var
)
->
GetMutable
<
Tensor
>
();
...
...
@@ -346,7 +344,7 @@ void RecurrentGradientAlgorithm::LinkBootMemoryGradients(
attr
.
boot_var
);
Tensor
*
boot_mem_grad
=
step_scope
->
CreateVariable
(
attr
.
boot_var
)
->
GetMutable
<
Tensor
>
();
if
(
infer_shape
)
{
if
(
infer_shape
_mode
)
{
boot_mem_grad
->
Resize
(
mem_grad
->
dims
());
}
else
{
boot_mem_grad
->
ShareDataWith
<
float
>
(
*
mem_grad
);
...
...
@@ -360,21 +358,20 @@ void RecurrentGradientAlgorithm::InferShape(
->
GetMutable
<
Tensor
>
()
->
dims
()[
0
];
auto
step_scopes
=
GetStepScopes
(
scope
);
rnn
::
SegmentInputs
(
step_scopes
,
arg_
->
inlinks
,
seq_len_
,
true
);
PADDLE_ENFORCE
(
scope
->
HasVariable
(
arg_
->
step_net
),
"step net is not in scope."
);
rnn
::
SegmentInputs
(
step_scopes
,
arg_
->
inlinks
,
seq_len_
,
true
/*infer_shape_mode*/
);
Variable
*
net
=
scope
->
GetVariable
(
arg_
->
step_net
);
PADDLE_ENFORCE
(
net
!=
nullptr
,
"failed to get step net"
);
for
(
int
step_id
=
seq_len_
-
1
;
step_id
>=
0
;
--
step_id
)
{
if
(
static_cast
<
size_t
>
(
step_id
)
!=
seq_len_
-
1
)
{
rnn
::
LinkMemories
(
step_scopes
,
arg_
->
memories
,
step_id
,
1
,
true
);
rnn
::
LinkMemories
(
step_scopes
,
arg_
->
memories
,
step_id
,
1
,
true
/*infer_shape_mode*/
);
}
net
->
GetMutable
<
NetOp
>
()
->
InferShape
(
step_scopes
[
step_id
]);
}
rnn
::
ConcatOutputs
(
step_scopes
,
arg_
->
outlinks
,
seq_len_
,
true
);
LinkBootMemoryGradients
(
step_scopes
[
0
],
true
);
rnn
::
ConcatOutputs
(
step_scopes
,
arg_
->
outlinks
,
seq_len_
,
true
/*infer_shape_mode*/
);
LinkBootMemoryGradients
(
step_scopes
[
0
],
true
/*infer_shape_mode*/
);
}
void
RecurrentGradientOp
::
Init
()
{
...
...
paddle/operators/recurrent_network_op.h
浏览文件 @
8925295a
...
...
@@ -73,7 +73,7 @@ struct ArgumentName {
void
SegmentInputs
(
std
::
vector
<
std
::
shared_ptr
<
Scope
>>&
step_scopes
,
const
std
::
vector
<
Link
>&
inlinks
,
const
size_t
seq_len
,
bool
infer_shape
);
bool
infer_shape
_mode
);
/**
* Process outputs of step nets and merge to variables.
...
...
@@ -81,13 +81,13 @@ void SegmentInputs(std::vector<std::shared_ptr<Scope>>& step_scopes,
void
ConcatOutputs
(
std
::
vector
<
std
::
shared_ptr
<
Scope
>>&
step_scopes
,
const
std
::
vector
<
Link
>&
outlinks
,
const
size_t
seq_len
,
bool
infer_shape
);
bool
infer_shape
_mode
);
void
LinkMemories
(
std
::
vector
<
std
::
shared_ptr
<
Scope
>>&
step_scopes
,
const
std
::
vector
<
MemoryAttr
>&
memories
,
const
size_t
step_id
,
const
int
offset
,
bool
infer_shape
);
bool
infer_shape
_mode
);
void
InitArgument
(
const
ArgumentName
&
name
,
Argument
*
arg
);
...
...
@@ -128,7 +128,8 @@ protected:
->
GetMutable
<
std
::
vector
<
std
::
shared_ptr
<
Scope
>>>
();
}
void
InitMemories
(
std
::
shared_ptr
<
Scope
>
step_scopes
,
bool
infer_shape
)
const
;
void
InitMemories
(
std
::
shared_ptr
<
Scope
>
step_scopes
,
bool
infer_shape_mode
)
const
;
private:
std
::
unique_ptr
<
rnn
::
Argument
>
arg_
;
...
...
@@ -153,7 +154,7 @@ public:
const
platform
::
DeviceContext
&
dev_ctx
)
const
;
void
LinkBootMemoryGradients
(
std
::
shared_ptr
<
Scope
>
step_scopes
,
bool
infer_shape
)
const
;
bool
infer_shape
_mode
)
const
;
/**
* InferShape must be called before Run.
...
...
paddle/operators/recurrent_network_op_test.cc
浏览文件 @
8925295a
...
...
@@ -298,7 +298,10 @@ protected:
std
::
vector
<
std
::
shared_ptr
<
Scope
>>*
step_scopes
=
scope_
->
GetVariable
(
"step_scopes"
)
->
GetMutable
<
std
::
vector
<
std
::
shared_ptr
<
Scope
>>>
();
rnn
::
SegmentInputs
(
*
step_scopes
,
std
::
vector
<
rnn
::
Link
>
{
inlink
},
10
,
true
);
rnn
::
SegmentInputs
(
*
step_scopes
,
std
::
vector
<
rnn
::
Link
>
{
inlink
},
10
,
true
/*infer_shape_mode*/
);
}
void
LinkeMemories
()
{
...
...
@@ -313,7 +316,8 @@ protected:
scope_
->
GetVariable
(
"step_scopes"
)
->
GetMutable
<
std
::
vector
<
std
::
shared_ptr
<
Scope
>>>
();
for
(
int
i
=
1
;
i
<
10
;
++
i
)
{
rnn
::
LinkMemories
(
*
step_scopes
,
memories
,
i
,
-
1
,
true
);
rnn
::
LinkMemories
(
*
step_scopes
,
memories
,
i
,
-
1
,
true
/*infer_shape_mode*/
);
}
}
...
...
@@ -343,7 +347,7 @@ TEST(RecurrentOp, LinkMemories) {
auto
tensor
=
scope
->
CreateVariable
(
"h"
)
->
GetMutable
<
Tensor
>
();
float
*
data
=
tensor
->
mutable_data
<
float
>
(
make_ddim
({
15
,
20
}),
CPUPlace
());
for
(
int
j
=
0
;
j
<
15
*
20
;
++
j
)
{
data
[
i
]
=
rand
()
*
(
1.
/
(
double
)
RAND_MAX
);
data
[
j
]
=
rand
()
*
(
1.
/
(
double
)
RAND_MAX
);
}
step_scopes
.
push_back
(
scope
);
}
...
...
@@ -357,7 +361,7 @@ TEST(RecurrentOp, LinkMemories) {
memories
.
push_back
(
mem_attr
);
for
(
int
i
=
1
;
i
<
len
;
++
i
)
{
rnn
::
LinkMemories
(
step_scopes
,
memories
,
i
,
-
1
,
false
);
rnn
::
LinkMemories
(
step_scopes
,
memories
,
i
,
-
1
,
false
/*infer_shape_mode*/
);
}
// check
for
(
int
i
=
0
;
i
<
len
-
1
;
++
i
)
{
...
...
@@ -373,7 +377,7 @@ TEST(RecurrentOp, LinkMemories) {
}
for
(
int
i
=
len
-
2
;
i
>=
0
;
--
i
)
{
rnn
::
LinkMemories
(
step_scopes
,
memories
,
i
,
1
,
false
);
rnn
::
LinkMemories
(
step_scopes
,
memories
,
i
,
1
,
false
/*infer_shape_mode*/
);
}
// check
for
(
int
i
=
len
-
2
;
i
>=
0
;
--
i
)
{
...
...
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