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体验新版 GitCode,发现更多精彩内容 >>
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c57954e7
编写于
2月 17, 2017
作者:
Q
qiaolongfei
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
use v2.layer in api_train_v2
上级
6dc6814f
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
26 addition
and
25 deletion
+26
-25
demo/mnist/api_train_v2.py
demo/mnist/api_train_v2.py
+18
-18
python/paddle/v2/__init__.py
python/paddle/v2/__init__.py
+3
-2
python/paddle/v2/layer.py
python/paddle/v2/layer.py
+5
-5
未找到文件。
demo/mnist/api_train_v2.py
浏览文件 @
c57954e7
from
paddle.trainer_config_helpers
import
*
from
paddle.trainer.PyDataProvider2
import
dense_vector
,
integer_value
import
paddle.v2
as
paddle
import
numpy
import
numpy
import
paddle.v2
as
paddle
from
paddle.trainer.PyDataProvider2
import
dense_vector
,
integer_value
import
mnist_util
import
mnist_util
...
@@ -12,32 +12,32 @@ def train_reader():
...
@@ -12,32 +12,32 @@ def train_reader():
yield
item
yield
item
def
network_config
():
imgs
=
data_layer
(
name
=
'pixel'
,
size
=
784
)
hidden1
=
fc_layer
(
input
=
imgs
,
size
=
200
)
hidden2
=
fc_layer
(
input
=
hidden1
,
size
=
200
)
inference
=
fc_layer
(
input
=
hidden2
,
size
=
10
,
act
=
SoftmaxActivation
())
cost
=
classification_cost
(
input
=
inference
,
label
=
data_layer
(
name
=
'label'
,
size
=
10
))
outputs
(
cost
)
def
main
():
def
main
():
paddle
.
init
(
use_gpu
=
False
,
trainer_count
=
1
)
paddle
.
init
(
use_gpu
=
False
,
trainer_count
=
1
)
topology
=
parse_network_config
(
network_config
)
# define network topology
images
=
paddle
.
layer
.
data
(
name
=
'pixel'
,
size
=
784
)
label
=
paddle
.
layer
.
data
(
name
=
'label'
,
size
=
10
)
hidden1
=
paddle
.
layer
.
fc
(
input
=
images
,
size
=
200
)
hidden2
=
paddle
.
layer
.
fc
(
input
=
hidden1
,
size
=
200
)
inference
=
paddle
.
layer
.
fc
(
input
=
hidden2
,
size
=
10
,
act
=
paddle
.
activation
.
Softmax
())
cost
=
paddle
.
layer
.
classification_cost
(
input
=
inference
,
label
=
label
)
topology
=
paddle
.
layer
.
parse_network
(
cost
)
print
topology
parameters
=
paddle
.
parameters
.
create
(
topology
)
parameters
=
paddle
.
parameters
.
create
(
topology
)
for
param_name
in
parameters
.
keys
():
for
param_name
in
parameters
.
keys
():
array
=
parameters
.
get
(
param_name
)
array
=
parameters
.
get
(
param_name
)
array
[:]
=
numpy
.
random
.
uniform
(
low
=-
1.0
,
high
=
1.0
,
size
=
array
.
shape
)
array
[:]
=
numpy
.
random
.
uniform
(
low
=-
1.0
,
high
=
1.0
,
size
=
array
.
shape
)
parameters
.
set
(
parameter_name
=
param_name
,
value
=
array
)
parameters
.
set
(
parameter_name
=
param_name
,
value
=
array
)
adam_optimizer
=
paddle
.
optimizer
.
Optimizer
(
adam_optimizer
=
paddle
.
optimizer
.
Adam
(
learning_rate
=
0.01
)
learning_rate
=
0.01
,
learning_method
=
AdamOptimizer
())
def
event_handler
(
event
):
def
event_handler
(
event
):
if
isinstance
(
event
,
paddle
.
event
.
EndIteration
):
if
isinstance
(
event
,
paddle
.
event
.
EndIteration
):
para
=
parameters
.
get
(
'___fc_
layer_
2__.w0'
)
para
=
parameters
.
get
(
'___fc_2__.w0'
)
print
"Pass %d, Batch %d, Cost %f, Weight Mean Of Fc 2 is %f"
%
(
print
"Pass %d, Batch %d, Cost %f, Weight Mean Of Fc 2 is %f"
%
(
event
.
pass_id
,
event
.
batch_id
,
event
.
cost
,
para
.
mean
())
event
.
pass_id
,
event
.
batch_id
,
event
.
cost
,
para
.
mean
())
...
...
python/paddle/v2/__init__.py
浏览文件 @
c57954e7
...
@@ -19,8 +19,9 @@ import trainer
...
@@ -19,8 +19,9 @@ import trainer
import
event
import
event
import
py_paddle.swig_paddle
as
api
import
py_paddle.swig_paddle
as
api
__all__
=
[
__all__
=
[
'optimizer'
,
'layer'
,
'activation'
,
'parameters'
,
'init'
,
'trainer'
,
'event'
]
'optimizer'
,
'layer'
,
'activation'
,
'parameters'
,
'init'
,
'trainer'
,
'event'
]
def
init
(
**
kwargs
):
def
init
(
**
kwargs
):
...
...
python/paddle/v2/layer.py
浏览文件 @
c57954e7
...
@@ -72,6 +72,11 @@ from paddle.trainer_config_helpers.config_parser_utils import \
...
@@ -72,6 +72,11 @@ from paddle.trainer_config_helpers.config_parser_utils import \
from
paddle.trainer_config_helpers.default_decorators
import
wrap_name_default
from
paddle.trainer_config_helpers.default_decorators
import
wrap_name_default
import
collections
import
collections
__all__
=
[
'parse_network'
,
'data'
,
'fc'
,
'max_id'
,
'classification_cost'
,
'cross_entropy_cost'
]
def
parse_network
(
*
outputs
):
def
parse_network
(
*
outputs
):
"""
"""
...
@@ -165,11 +170,6 @@ cross_entropy_cost = __convert_to_v2__(
...
@@ -165,11 +170,6 @@ cross_entropy_cost = __convert_to_v2__(
name_prefix
=
'cross_entropy'
,
name_prefix
=
'cross_entropy'
,
parent_names
=
[
'input'
,
'label'
])
parent_names
=
[
'input'
,
'label'
])
__all__
=
[
'parse_network'
,
'data'
,
'fc'
,
'max_id'
,
'classification_cost'
,
'cross_entropy_cost'
]
if
__name__
==
'__main__'
:
if
__name__
==
'__main__'
:
pixel
=
data
(
name
=
'pixel'
,
size
=
784
)
pixel
=
data
(
name
=
'pixel'
,
size
=
784
)
label
=
data
(
name
=
'label'
,
size
=
10
)
label
=
data
(
name
=
'label'
,
size
=
10
)
...
...
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