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be4c0123
编写于
8月 28, 2017
作者:
C
caoying03
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python/paddle/v2/parameters.py
python/paddle/v2/parameters.py
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python/paddle/v2/parameters.py
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@@ -43,9 +43,26 @@ def create(layers):
class
Parameters
(
object
):
"""
Parameters is a dictionary contains Paddle's parameter. The key of
Parameters is the name of parameter. The value of Parameters is a plain
:code:`numpy.ndarry` .
`Parameters` manages all the learnable parameters in a neural network.
It stores parameters' information in an OrderedDict, key of which is
the name of a parameter, and value related to a key is a parameter's
configuration, such as initialization mean and std, its size, whether it is
a static parameter, and so on.
:param __param_conf__: this member stores the configurations of learnable
parameters in a network in an OrderedDict. The parameters are added by
following their creation order in the neural network one by one:
parameters of the previous layers in a network are careted first.
When a user iterates over this dict, he can visit parameters in the
network from button to up.
:type __param_conf__: OrderedDict
:param __gradient_machines__: all of the parameters in a neural network are
appended to a Paddle gradient machine, which is used internally to copy
the parameter values between the C++ and Python end.
:type __gradient_machines__: list
:param __tmp_params__: a dict to store dummy parameters if no
__gradient_machines__ is appended to `Parameters`.
:type __tmp_params__: dict
Basically usage is
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