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体验新版 GitCode,发现更多精彩内容 >>
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892cc82d
编写于
4月 12, 2017
作者:
Y
Yu Yang
提交者:
GitHub
4月 12, 2017
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差异文件
Merge pull request #1766 from reyoung/feature/add_list_type_of_feeding
Add list type of feeding
上级
fbea3918
66f5052c
变更
2
隐藏空白更改
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Showing
2 changed file
with
30 addition
and
8 deletion
+30
-8
python/paddle/v2/data_feeder.py
python/paddle/v2/data_feeder.py
+29
-7
python/paddle/v2/trainer.py
python/paddle/v2/trainer.py
+1
-1
未找到文件。
python/paddle/v2/data_feeder.py
浏览文件 @
892cc82d
...
...
@@ -13,7 +13,7 @@
# limitations under the License.
from
py_paddle
import
DataProviderConverter
import
collections
import
paddle.trainer.PyDataProvider2
as
pydp2
__all__
=
[
'DataFeeder'
]
...
...
@@ -35,15 +35,30 @@ class DataFeeder(DataProviderConverter):
DataFeeder converts this mini-batch data entries into Arguments in order
to feed it to C++ interface.
The example usage:
The simple usage shows below
.. code-block:: python
feeding = ['image', 'label']
data_types = enumerate_data_types_of_data_layers(topology)
feeder = DataFeeder(data_types=data_types, feeding=feeding)
minibatch_data = [([1.0, 2.0, 3.0, ...], 5)]
arg = feeder(minibatch_data)
If mini-batch data and data layers are not one to one mapping, we
could pass a dictionary to feeding parameter to represent the mapping
relationship.
.. code-block:: python
data_types = [('image', paddle.data_type.dense_vector(784)),
('label', paddle.data_type.integer_value(10))]
reader_dict
= {'image':0, 'label':1}
feeder = DataFeeder(data_types=data_types,
reader_dict=reader_dict
)
feeding
= {'image':0, 'label':1}
feeder = DataFeeder(data_types=data_types,
feeding=feeding
)
minibatch_data = [
( [1.0,2.0,3.0,4.0], 5, [6,7,8] ), # first sample
( [1.0,2.0,3.0,4.0], 5, [6,7,8] ) # second sample
...
...
@@ -65,9 +80,9 @@ class DataFeeder(DataProviderConverter):
a tuple of (data_name, data_type).
:type data_types: list
:param
reader_dict: A dictionary to specify the position of each data
in the input data.
:type feeding: dict
:param
feeding: A dictionary or a sequence to specify the position of each
data
in the input data.
:type feeding: dict
|collections.Sequence|None
"""
def
__init__
(
self
,
data_types
,
feeding
=
None
):
...
...
@@ -75,6 +90,13 @@ class DataFeeder(DataProviderConverter):
input_types
=
[]
if
feeding
is
None
:
feeding
=
default_feeding_map
(
data_types
)
elif
isinstance
(
feeding
,
collections
.
Sequence
):
feed_list
=
feeding
feeding
=
dict
()
for
i
,
name
in
enumerate
(
feed_list
):
feeding
[
name
]
=
i
elif
not
isinstance
(
feeding
,
dict
):
raise
TypeError
(
"Feeding should be dict or sequence or None."
)
self
.
feeding
=
feeding
for
each
in
data_types
:
...
...
python/paddle/v2/trainer.py
浏览文件 @
892cc82d
...
...
@@ -81,7 +81,7 @@ class SGD(object):
:type event_handler: (BaseEvent) => None
:param feeding: Feeding is a map of neural network input name and array
index that reader returns.
:type feeding: dict
:type feeding: dict
|list
:return:
"""
if
event_handler
is
None
:
...
...
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