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体验新版 GitCode,发现更多精彩内容 >>
提交
89cfb39f
编写于
2月 20, 2017
作者:
Q
qiaolongfei
浏览文件
操作
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电子邮件补丁
差异文件
use data_type of data layer
上级
772b476b
变更
3
显示空白变更内容
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并排
Showing
3 changed file
with
5 addition
and
5 deletion
+5
-5
demo/mnist/api_train.py
demo/mnist/api_train.py
+1
-1
demo/mnist/api_train_v2.py
demo/mnist/api_train_v2.py
+2
-2
python/paddle/v2/layer.py
python/paddle/v2/layer.py
+2
-2
未找到文件。
demo/mnist/api_train.py
浏览文件 @
89cfb39f
...
@@ -99,7 +99,7 @@ def main():
...
@@ -99,7 +99,7 @@ def main():
# DataProvider Converter is a utility convert Python Object to Paddle C++
# DataProvider Converter is a utility convert Python Object to Paddle C++
# Input. The input format is as same as Paddle's DataProvider.
# Input. The input format is as same as Paddle's DataProvider.
converter
=
DataProviderConverter
(
converter
=
DataProviderConverter
(
input_types
=
[
dp
.
dense_vector
(
784
),
dp
.
integer_value
(
10
)
])
input_types
=
[
images
.
data_type
,
label
.
data_type
])
train_file
=
'./data/raw_data/train'
train_file
=
'./data/raw_data/train'
test_file
=
'./data/raw_data/t10k'
test_file
=
'./data/raw_data/t10k'
...
...
demo/mnist/api_train_v2.py
浏览文件 @
89cfb39f
...
@@ -51,8 +51,8 @@ def main():
...
@@ -51,8 +51,8 @@ def main():
batch_size
=
32
,
# batch size should be refactor in Data reader
batch_size
=
32
,
# batch size should be refactor in Data reader
data_types
=
{
# data_types will be removed, It should be in
data_types
=
{
# data_types will be removed, It should be in
# network topology
# network topology
'pixel'
:
dense_vector
(
784
)
,
'pixel'
:
images
.
data_type
,
'label'
:
integer_value
(
10
)
'label'
:
label
.
data_type
})
})
...
...
python/paddle/v2/layer.py
浏览文件 @
89cfb39f
...
@@ -168,15 +168,15 @@ class DataLayerV2(Layer):
...
@@ -168,15 +168,15 @@ class DataLayerV2(Layer):
def
__init__
(
self
,
name
,
data_type
,
**
kwargs
):
def
__init__
(
self
,
name
,
data_type
,
**
kwargs
):
assert
isinstance
(
data_type
,
dp
.
InputType
)
assert
isinstance
(
data_type
,
dp
.
InputType
)
self
.
data_type
=
data_type
self
.
__method_name__
=
'data_layer'
self
.
__method_name__
=
'data_layer'
self
.
__kwargs__
=
kwargs
self
.
__kwargs__
=
kwargs
self
.
__data_size__
=
data_type
.
dim
super
(
DataLayerV2
,
self
).
__init__
(
name
=
name
,
parent_layers
=
dict
())
super
(
DataLayerV2
,
self
).
__init__
(
name
=
name
,
parent_layers
=
dict
())
def
to_proto_impl
(
self
,
**
kwargs
):
def
to_proto_impl
(
self
,
**
kwargs
):
args
=
dict
()
args
=
dict
()
args
[
'size'
]
=
self
.
__data_size__
args
[
'size'
]
=
self
.
data_type
.
dim
for
each
in
kwargs
:
for
each
in
kwargs
:
args
[
each
]
=
kwargs
[
each
]
args
[
each
]
=
kwargs
[
each
]
for
each
in
self
.
__kwargs__
:
for
each
in
self
.
__kwargs__
:
...
...
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