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体验新版 GitCode,发现更多精彩内容 >>
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22fba722
编写于
12月 21, 2017
作者:
K
kavyasrinet
提交者:
GitHub
12月 21, 2017
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差异文件
Add doc for data layer (#6858)
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a5523859
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python/paddle/v2/fluid/layers/io.py
python/paddle/v2/fluid/layers/io.py
+20
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python/paddle/v2/fluid/layers/io.py
浏览文件 @
22fba722
...
...
@@ -12,20 +12,9 @@ def data(name,
type
=
core
.
VarDesc
.
VarType
.
LOD_TENSOR
,
stop_gradient
=
True
):
"""
Data Layer.
**Data Layer**
Args:
name: The name/alias of the function
shape: Tuple declaring the shape.
append_batch_size: Whether or not to append the data as a batch.
dtype: The type of data : float32, float_16, int etc
type: The output type. By default it is LOD_TENSOR.
lod_level(int): The LoD Level. 0 means the input data is not a sequence.
main_program: Name of the main program that calls this
startup_program: Name of the startup program
stop_gradient: A boolean that mentions whether gradient should flow.
This function takes in input and based on whether data has
This function takes in the input and based on whether data has
to be returned back as a minibatch, it creates the global variable using
the helper functions. The global variables can be accessed by all the
following operations and layers in the graph.
...
...
@@ -33,6 +22,24 @@ def data(name,
All the input variables of this function are passed in as local variables
to the LayerHelper constructor.
Args:
name(str): The name/alias of the function
shape(list): Tuple declaring the shape.
append_batch_size(bool): Whether or not to append the data as a batch.
dtype(int|float): The type of data : float32, float_16, int etc
type(VarType): The output type. By default it is LOD_TENSOR.
lod_level(int): The LoD Level. 0 means the input data is not a sequence.
main_program(Program): Name of the main program that calls this
startup_program(Program): Name of the startup program
stop_gradient(bool): A boolean that mentions whether gradient should flow.
Returns:
Variable: The global variable that gives access to the data.
Examples:
.. code-block:: python
data = fluid.layers.data(name='x', shape=[784], dtype='float32')
"""
helper
=
LayerHelper
(
'data'
,
**
locals
())
shape
=
list
(
shape
)
...
...
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