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release 1.3.1
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docs/conf.py

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# built documents.
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#
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# The short X.Y version.
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version = '1.3.0'
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version = '1.3.1'
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# The full version, including alpha/beta/rc tags.
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release = '1.3.0'
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release = '1.3.1'
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# The language for content autogenerated by Sphinx. Refer to documentation
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# for a list of supported languages.
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# The name for this set of Sphinx documents.
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# "<project> v<release> documentation" by default.
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#
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# html_title = 'TensorLayer v1.3.0'
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# html_title = 'TensorLayer v1.3.1'
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# A shorter title for the navigation bar. Default is the same as html_title.
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#

setup.py

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setup(
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name = "tensorlayer",
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version = "1.3.0",
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version = "1.3.1",
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include_package_data=True,
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author='TensorLayer Contributors',
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author_email='[email protected]',

tensorlayer/__init__.py

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from . import rein
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__version__ = "1.3.0"
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__version__ = "1.3.1"

tensorlayer/layers.py

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@@ -1940,8 +1940,7 @@ def mean_var_with_update():
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self.all_params.extend( variables )
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# self.all_params.extend( [beta, gamma] )
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class BatchNormLayer5(Layer): #
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class BatchNormLayer5(Layer): # Akara
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"""
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The :class:`BatchNormLayer` class is a normalization layer, see ``tf.nn.batch_normalization`` and ``tf.nn.moments``.
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self.all_params.extend( variables )
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# self.all_params.extend( [beta, gamma] )
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# class BatchNormLayer4(Layer): # work TFlearn https://github.com/tflearn/tflearn/blob/master/tflearn/layers/normalization.py
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# """
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# The :class:`BatchNormLayer` class is a normalization layer, see ``tf.nn.batch_normalization`` and ``tf.nn.moments``.

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