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体验新版 GitCode,发现更多精彩内容 >>
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0cb8a666
编写于
5月 26, 2017
作者:
X
xuwei06
浏览文件
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电子邮件补丁
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7d0355cd
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1
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1 changed file
with
20 addition
and
20 deletion
+20
-20
python/paddle/v2/layer.py
python/paddle/v2/layer.py
+20
-20
未找到文件。
python/paddle/v2/layer.py
浏览文件 @
0cb8a666
...
...
@@ -40,6 +40,7 @@ from paddle.proto.ModelConfig_pb2 import ModelConfig, SubModelConfig
__all__
=
[
'data'
,
'parse_network'
]
__layer_map__
=
{}
def
__wrap__
(
f
):
def
wrapped
(
*
args
,
**
xargs
):
out
=
f
(
*
args
,
**
xargs
)
...
...
@@ -53,6 +54,7 @@ def __wrap__(f):
return
wrapped
def
__need_to_keep__
(
name
):
if
name
in
[
'StaticInput'
,
'LayerType'
,
'layer_support'
]:
return
False
...
...
@@ -99,6 +101,7 @@ def __data_layer__(name, type, **kwargs):
l
.
data_type
=
type
return
l
data
=
__wrap__
(
__data_layer__
)
LayerV2
=
v1_layers
.
LayerOutput
...
...
@@ -107,6 +110,7 @@ LayerV2 = v1_layers.LayerOutput
def
__get_used_layers__
(
output_layers
,
extra_layers
=
None
):
layer_names
=
set
()
parents
=
{}
def
add_parent
(
child
,
parent
):
if
child
in
parents
:
parents
[
child
].
append
(
parent
)
...
...
@@ -181,28 +185,25 @@ def __get_used_evaluators__(layer_names):
return
evaluator_names
def
__trim_submodel__
(
old_submodel
,
layer_names
,
input_layer_names
,
output_layer_names
,
evaluator_names
):
def
__trim_submodel__
(
old_submodel
,
layer_names
,
input_layer_names
,
output_layer_names
,
evaluator_names
):
submodel
=
SubModelConfig
()
submodel
.
name
=
old_submodel
.
name
submodel
.
layer_names
.
extend
(
filter
(
lambda
x
:
x
in
layer_names
,
old_submodel
.
layer_names
))
submodel
.
input_layer_names
.
extend
(
filter
(
lambda
x
:
x
in
input_layer_names
,
submodel
.
layer_names
))
submodel
.
output_layer_names
.
extend
(
filter
(
lambda
x
:
x
in
output_layer_names
,
submodel
.
layer_names
))
submodel
.
evaluator_names
.
extend
(
filter
(
lambda
x
:
x
in
evaluator_names
,
old_submodel
.
evaluator_names
))
submodel
.
layer_names
.
extend
(
filter
(
lambda
x
:
x
in
layer_names
,
old_submodel
.
layer_names
))
submodel
.
input_layer_names
.
extend
(
filter
(
lambda
x
:
x
in
input_layer_names
,
submodel
.
layer_names
))
submodel
.
output_layer_names
.
extend
(
filter
(
lambda
x
:
x
in
output_layer_names
,
submodel
.
layer_names
))
submodel
.
evaluator_names
.
extend
(
filter
(
lambda
x
:
x
in
evaluator_names
,
old_submodel
.
evaluator_names
))
submodel
.
is_recurrent_layer_group
=
old_submodel
.
is_recurrent_layer_group
submodel
.
reversed
=
old_submodel
.
reversed
submodel
.
memories
.
extend
(
filter
(
lambda
x
:
x
.
link_name
in
layer_names
,
old_submodel
.
memories
))
submodel
.
memories
.
extend
(
filter
(
lambda
x
:
x
.
link_name
in
layer_names
,
old_submodel
.
memories
))
target_inlinkid
=
(
old_submodel
.
target_inlinkid
if
old_submodel
.
HasField
(
'target_inlinkid'
)
else
-
1
)
in_links
=
[]
...
...
@@ -213,8 +214,8 @@ def __trim_submodel__(old_submodel,
target_inlinkid
=
len
(
in_links
)
-
1
submodel
.
in_links
.
extend
(
in_links
)
submodel
.
out_links
.
extend
(
filter
(
lambda
x
:
x
.
link_name
in
layer_names
,
old_submodel
.
out_links
))
submodel
.
out_links
.
extend
(
filter
(
lambda
x
:
x
.
link_name
in
layer_names
,
old_submodel
.
out_links
))
if
old_submodel
.
HasField
(
'generator'
):
submodel
.
generator
.
CopyFrom
(
old_submodel
.
generator
)
...
...
@@ -264,9 +265,8 @@ def parse_network(output_layers, extra_layers=None):
for
s
in
cp
.
g_config
.
model_config
.
sub_models
:
if
s
.
name
in
submodel_names
:
s
=
__trim_submodel__
(
s
,
layer_names
,
input_layer_names
,
output_layer_names
,
evaluator_names
)
s
=
__trim_submodel__
(
s
,
layer_names
,
input_layer_names
,
output_layer_names
,
evaluator_names
)
model_config
.
sub_models
.
extend
([
s
])
return
model_config
...
...
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