Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
wmsofts
Paddle
提交
7665bdba
P
Paddle
项目概览
wmsofts
/
Paddle
与 Fork 源项目一致
Fork自
PaddlePaddle / Paddle
通知
1
Star
0
Fork
0
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
0
列表
看板
标记
里程碑
合并请求
0
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
Paddle
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
0
Issue
0
列表
看板
标记
里程碑
合并请求
0
合并请求
0
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
体验新版 GitCode,发现更多精彩内容 >>
提交
7665bdba
编写于
8月 07, 2017
作者:
Y
Yan Chunwei
提交者:
GitHub
8月 07, 2017
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Rnn forward logic test (#3291)
* finish forward debug
上级
ec2c753c
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
98 addition
and
69 deletion
+98
-69
paddle/framework/operator.h
paddle/framework/operator.h
+5
-1
paddle/operators/add_op.cc
paddle/operators/add_op.cc
+2
-2
paddle/operators/mul_op.cc
paddle/operators/mul_op.cc
+9
-5
paddle/operators/recurrent_op.cc
paddle/operators/recurrent_op.cc
+19
-7
paddle/operators/rnn/recurrent_op_utils.cc
paddle/operators/rnn/recurrent_op_utils.cc
+15
-12
python/paddle/v2/framework/tests/test_recurrent_op.py
python/paddle/v2/framework/tests/test_recurrent_op.py
+48
-42
未找到文件。
paddle/framework/operator.h
浏览文件 @
7665bdba
...
...
@@ -174,7 +174,11 @@ class OperatorContext {
template
<
typename
T
>
T
*
Output
(
const
size_t
index
)
const
{
auto
var
=
OutputVar
(
index
);
PADDLE_ENFORCE
(
var
!=
nullptr
,
"Output(%d) should not be nullptr"
,
index
);
PADDLE_ENFORCE
(
var
!=
nullptr
,
"Output(%d) not be nullptr, which means variable [%s] does not "
"exist in scope"
,
index
,
op_
.
outputs_
[
index
]);
return
var
->
GetMutable
<
T
>
();
}
...
...
paddle/operators/add_op.cc
浏览文件 @
7665bdba
...
...
@@ -20,8 +20,8 @@ namespace operators {
class
AddOp
:
public
OperatorWithKernel
{
protected:
void
InferShape
(
const
InferShapeContext
&
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
.
InputSize
()
==
2
,
"Input size of AddOp must be two"
);
PADDLE_ENFORCE
(
ctx
.
OutputSize
()
==
1
,
"Output size of AddOp must be one"
);
PADDLE_ENFORCE
_EQ
(
ctx
.
InputSize
(),
2
);
PADDLE_ENFORCE
_EQ
(
ctx
.
OutputSize
(),
1
);
PADDLE_ENFORCE
(
ctx
.
InputVar
(
0
)
!=
nullptr
&&
ctx
.
InputVar
(
1
)
!=
nullptr
,
"Inputs of AddOp must all be set"
);
PADDLE_ENFORCE
(
ctx
.
OutputVar
(
0
)
!=
nullptr
,
...
...
paddle/operators/mul_op.cc
浏览文件 @
7665bdba
...
...
@@ -23,12 +23,16 @@ class MulOp : public OperatorWithKernel {
PADDLE_ENFORCE
(
ctx
.
InputSize
()
==
2
,
"The mul op must take two inputs"
);
auto
dim0
=
ctx
.
Input
<
Tensor
>
(
0
)
->
dims
();
auto
dim1
=
ctx
.
Input
<
Tensor
>
(
1
)
->
dims
();
PADDLE_ENFORCE
(
dim0
.
size
()
==
2
&&
dim1
.
size
()
==
2
,
"The input of mul op must be matrix"
);
PADDLE_ENFORCE
(
dim0
[
1
]
==
dim1
[
0
],
PADDLE_ENFORCE_EQ
(
dim0
.
size
(),
2
,
"input X(%s) should be a tensor with 2 dims, a matrix"
,
ctx
.
op_
.
Input
(
"X"
));
PADDLE_ENFORCE_EQ
(
dim1
.
size
(),
2
,
"input Y(%s) should be a tensor with 2 dims, a matrix"
,
ctx
.
op_
.
Input
(
"Y"
));
PADDLE_ENFORCE_EQ
(
dim0
[
1
],
dim1
[
0
],
"First matrix's width must be equal with second matrix's height."
);
PADDLE_ENFORCE
(
ctx
.
OutputSize
()
==
1
,
"The mul op must take
one output"
);
PADDLE_ENFORCE
_EQ
(
ctx
.
OutputSize
(),
1
,
"The mul op takes only
one output"
);
ctx
.
Output
<
Tensor
>
(
0
)
->
Resize
({
dim0
[
0
],
dim1
[
1
]});
}
};
...
...
paddle/operators/recurrent_op.cc
浏览文件 @
7665bdba
...
...
@@ -36,6 +36,7 @@ void RecurrentAlgorithm::InferShape(const Scope& scope) const {
InitMemories
(
step_scopes
[
0
],
true
/*infer_shape_mode*/
);
Variable
*
net
=
scope
.
FindVar
(
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
,
...
...
@@ -56,6 +57,7 @@ void RecurrentAlgorithm::Run(const Scope& scope,
Variable
*
net
=
scope
.
FindVar
(
arg_
->
step_net
);
for
(
size_t
step_id
=
0
;
step_id
<
seq_len_
;
step_id
++
)
{
// create output alias variables
if
(
step_id
>
0
)
{
rnn
::
LinkMemories
(
step_scopes
,
arg_
->
memories
,
step_id
,
-
1
,
false
/*infer_shape_mode*/
);
...
...
@@ -67,22 +69,31 @@ void RecurrentAlgorithm::Run(const Scope& scope,
}
void
RecurrentAlgorithm
::
CreateScopes
(
const
Scope
&
scope
)
const
{
// TODO(
xxx
) Only two scopes are needed for inference, this case will be
// TODO(
superjom
) Only two scopes are needed for inference, this case will be
// supported later.
auto
step_scopes
=
scope
.
FindVar
(
arg_
->
step_scopes
)
->
GetMutable
<
std
::
vector
<
Scope
*>>
();
auto
step_scopes_var
=
scope
.
FindVar
(
arg_
->
step_scopes
);
PADDLE_ENFORCE
(
step_scopes_var
!=
nullptr
,
""
);
auto
step_scopes
=
step_scopes_var
->
GetMutable
<
std
::
vector
<
Scope
*>>
();
// Now all variables in scope must be created outside of op.
auto
net_var
=
scope
.
FindVar
(
arg_
->
step_net
);
PADDLE_ENFORCE
(
net_var
!=
nullptr
,
"no stepnet called %s in scope"
,
arg_
->
step_net
);
auto
net_op
=
net_var
->
GetMutable
<
NetOp
>
();
PADDLE_ENFORCE
(
!
net_op
->
outputs_
.
empty
(),
"net_op has no outputs"
);
if
(
seq_len_
>
step_scopes
->
size
())
{
for
(
size_t
i
=
step_scopes
->
size
();
i
<
seq_len_
;
++
i
)
{
auto
&
step_scope
=
scope
.
NewScope
();
// Now all variables in scope must be created outside of op.
auto
net_op
=
scope
.
FindVar
(
arg_
->
step_net
)
->
GetMutable
<
NetOp
>
();
// create step net's temp inputs
for
(
auto
&
input
:
net_op
->
inputs_
)
{
// the weight are located in parent scope
if
(
!
step_scope
.
FindVar
(
input
))
step_scope
.
NewVar
(
input
);
if
(
!
step_scope
.
FindVar
(
input
))
step_scope
.
NewVar
(
input
)
->
GetMutable
<
Tensor
>
();
}
for
(
auto
&
output
:
net_op
->
outputs_
)
{
// create stepnet's outputs
for
(
const
auto
&
output
:
net_op
->
outputs_
)
{
step_scope
.
NewVar
(
output
);
}
step_scopes
->
emplace_back
(
&
step_scope
);
...
...
@@ -100,6 +111,7 @@ void RecurrentAlgorithm::InitMemories(Scope* step_scope,
Tensor
*
boot_mem
=
step_scope
->
FindVar
(
attr
.
boot_var
)
->
GetMutable
<
Tensor
>
();
if
(
infer_shape_mode
)
{
pre_mem
->
Resize
(
boot_mem
->
dims
());
PADDLE_ENFORCE_EQ
(
pre_mem
->
dims
().
size
(),
2
);
}
else
{
pre_mem
->
ShareDataWith
<
float
>
(
*
boot_mem
);
}
...
...
paddle/operators/rnn/recurrent_op_utils.cc
浏览文件 @
7665bdba
...
...
@@ -53,11 +53,13 @@ void ConcatOutputs(const std::vector<Scope*>& step_scopes,
PADDLE_ENFORCE
(
output_var
!=
nullptr
,
"output link [%s] is not in scope."
,
outlinks
[
i
].
external
);
Tensor
*
output
=
output_var
->
GetMutable
<
Tensor
>
();
if
(
infer_shape_mode
)
{
fmw
::
DDim
step_dims
=
step_scopes
[
0
]
->
FindVar
(
outlinks
[
i
].
internal
)
->
GetMutable
<
Tensor
>
()
->
dims
();
auto
step_scope_var
=
step_scopes
[
0
]
->
FindVar
(
outlinks
[
i
].
internal
);
PADDLE_ENFORCE
(
step_scope_var
!=
nullptr
,
"%s not in scope"
,
outlinks
[
i
].
internal
);
fmw
::
DDim
step_dims
=
step_scope_var
->
template
GetMutable
<
Tensor
>()
->
dims
();
std
::
vector
<
int
>
dims_vec
=
vectorize
(
step_dims
);
dims_vec
.
insert
(
dims_vec
.
begin
(),
seq_len
);
output
->
Resize
(
fmw
::
make_ddim
(
dims_vec
));
...
...
@@ -79,14 +81,15 @@ void LinkMemories(const std::vector<Scope*>& scopes,
const
std
::
vector
<
rnn
::
MemoryAttr
>&
memories
,
const
size_t
step_id
,
const
int
offset
,
bool
infer_shape_mode
)
{
PADDLE_ENFORCE
(
step_id
<
scopes
.
size
(),
"step [%d] is out of range of step scopes' size [%d]"
,
step_id
,
scopes
.
size
());
PADDLE_ENFORCE
(
static_cast
<
int
>
(
step_id
)
+
offset
>=
0
,
"offset [%d] must be large than -[%d]"
,
offset
,
step_id
);
PADDLE_ENFORCE
(
step_id
+
offset
<
scopes
.
size
(),
"offset [%d] is out of range, it must be less than (%d - %d)"
,
offset
,
scopes
.
size
(),
step_id
);
PADDLE_ENFORCE_LT
(
step_id
,
scopes
.
size
(),
"step [%d] is out of range of step scopes' size [%d]"
,
step_id
,
scopes
.
size
());
PADDLE_ENFORCE_GE
(
static_cast
<
int
>
(
step_id
)
+
offset
,
0
,
"offset [%d] must be large than -[%d]"
,
offset
,
step_id
);
PADDLE_ENFORCE_LT
(
step_id
+
offset
,
scopes
.
size
(),
"offset [%d] is out of range, it must be less than (%d - %d)"
,
offset
,
scopes
.
size
(),
step_id
);
auto
scope
=
scopes
[
step_id
];
auto
linked_scope
=
scopes
[
step_id
+
offset
];
for
(
auto
&
attr
:
memories
)
{
...
...
python/paddle/v2/framework/tests/test_recurrent_op.py
浏览文件 @
7665bdba
import
logging
import
paddle.v2.framework.core
as
core
import
unittest
import
numpy
as
np
...
...
@@ -7,10 +8,9 @@ ops = creation.op_creations
def
create_tensor
(
scope
,
name
,
shape
):
tensor
=
scope
.
create
_var
(
name
).
get_tensor
()
tensor
=
scope
.
new
_var
(
name
).
get_tensor
()
tensor
.
set_dims
(
shape
)
tensor
.
alloc_float
()
tensor
.
set
(
np
.
random
.
random
(
shape
))
tensor
.
set
(
np
.
random
.
random
(
shape
),
core
.
CPUPlace
())
return
tensor
...
...
@@ -31,40 +31,36 @@ class TestRNN(unittest.TestCase):
- h
'''
input_dim
=
30
batch_size
=
50
weight_dim
=
15
sent_len
=
11
def
init
(
self
):
input_dim
=
30
batch_size
=
50
weight_dim
=
15
self
.
scope
=
core
.
Scope
(
None
)
# create vars
create_tensor
(
self
.
scope
,
"x"
,
[
batch_size
,
input_dim
])
create_tensor
(
self
.
scope
,
"W"
,
[
input_dim
,
weight_dim
])
create_tensor
(
self
.
scope
,
"U"
,
[
weight_dim
,
weight_dim
])
create_tensor
(
self
.
scope
,
"h_boot"
,
[
batch_size
,
weight_dim
])
x_alias
=
"x@alias"
y_alias
=
"y@alias"
memory
=
"h@alias"
prememory
=
"h@pre"
output
=
"rnn_out"
output_alias
=
"rnn_out@alias"
# create step net
stepnet_var
=
self
.
scope
.
create_var
(
"stepnet"
)
stepnet
=
stepnet_var
.
get_net
()
# stepnet = core.Net.create()
x_fc_op
=
ops
.
fc
(
X
=
x_alias
,
W
=
"W"
,
Y
=
"Wx"
)
h_fc_op
=
ops
.
fc
(
X
=
prememory
,
W
=
"U"
,
Y
=
"Uh"
)
sum_op
=
ops
.
add_two
(
X
=
"Wx"
,
Y
=
"Uh"
,
Out
=
"sum"
)
sig_op
=
ops
.
sigmoid
(
X
=
"sum"
,
Y
=
memory
)
stepnet
.
add_op
(
x_fc_op
)
stepnet
.
add_op
(
h_fc_op
)
stepnet
.
add_op
(
sum_op
)
stepnet
.
add_op
(
sig_op
)
stepnet
.
complete_add_op
(
True
)
self
.
scope
=
core
.
Scope
()
self
.
create_global_variables
()
self
.
create_step_net
()
rnn_op
=
self
.
create_rnn_op
()
ctx
=
core
.
DeviceContext
.
create
(
core
.
CPUPlace
())
print
'infer_shape'
rnn_op
.
infer_shape
(
self
.
scope
)
rnn_op
.
run
(
self
.
scope
,
ctx
)
def
create_global_variables
(
self
):
# create inlink
create_tensor
(
self
.
scope
,
"x"
,
[
self
.
sent_len
,
self
.
batch_size
,
self
.
input_dim
])
create_tensor
(
self
.
scope
,
"W"
,
[
self
.
input_dim
,
self
.
input_dim
])
create_tensor
(
self
.
scope
,
"U"
,
[
self
.
input_dim
,
self
.
input_dim
])
create_tensor
(
self
.
scope
,
"h_boot"
,
[
self
.
batch_size
,
self
.
input_dim
])
self
.
scope
.
new_var
(
"step_scopes"
)
self
.
scope
.
new_var
(
"h@alias"
)
self
.
scope
.
new_var
(
"h"
)
def
create_rnn_op
(
self
):
# create RNNOp
rnnop
=
ops
.
recurrent_op
(
# inputs
...
...
@@ -72,17 +68,27 @@ class TestRNN(unittest.TestCase):
boot_memories
=
[
"h_boot"
],
step_net
=
"stepnet"
,
# outputs
outlinks
=
[
output
],
outlinks
=
[
"h"
],
step_scopes
=
"step_scopes"
,
# attributes
inlink_alias
=
[
"x@alias"
],
outlink_alias
=
[
output_alias
],
pre_memories
=
[
prememory
],
memories
=
[
memory
])
outlink_alias
=
[
"h@alias"
],
pre_memories
=
[
"h@pre"
],
memories
=
[
"h@alias"
])
return
rnnop
def
create_step_net
(
self
):
var
=
self
.
scope
.
new_var
(
"stepnet"
)
stepnet
=
var
.
get_net
()
ctx
=
core
.
DeviceContext
.
cpu_context
()
rnnop
.
infer_shape
(
self
.
scope
)
rnnop
.
run
(
self
.
scope
,
ctx
)
x_fc_op
=
ops
.
fc
(
X
=
"x@alias"
,
W
=
"W"
,
Y
=
"Wx"
)
h_fc_op
=
ops
.
fc
(
X
=
"h@pre"
,
W
=
"U"
,
Y
=
"Uh"
)
sum_op
=
ops
.
add_two
(
X
=
"Wx"
,
Y
=
"Uh"
,
Out
=
"sum"
)
sig_op
=
ops
.
sigmoid
(
X
=
"sum"
,
Y
=
"h@alias"
)
for
op
in
[
x_fc_op
,
h_fc_op
,
sum_op
,
sig_op
]:
stepnet
.
add_op
(
op
)
stepnet
.
complete_add_op
(
True
)
def
test_recurrent
(
self
):
self
.
init
()
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录