release 1.4.5

tensorlayer · May 18, 2017 · a96c7d8 · a96c7d8
1 parent 2b83e1b
commit a96c7d8
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Showing 4 changed files with 7 additions and 7 deletions.
diff --git a/docs/conf.py b/docs/conf.py
@@ -67,9 +67,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = '1.4.4'
+version = '1.4.5'
 # The full version, including alpha/beta/rc tags.
-release = '1.4.4'
+release = '1.4.5'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.
@@ -143,7 +143,7 @@
 # The name for this set of Sphinx documents.
 # "<project> v<release> documentation" by default.
 #
-# html_title = 'TensorLayer v1.4.3'
+# html_title = 'TensorLayer v1.4.5'
 
 # A shorter title for the navigation bar.  Default is the same as html_title.
 #

diff --git a/setup.py b/setup.py
@@ -10,7 +10,7 @@
 
 setup(
     name = "tensorlayer",
-    version = "1.4.4",
+    version = "1.4.5",
     include_package_data=True,
     author='TensorLayer Contributors',
     author_email='[email protected]',

diff --git a/tensorlayer/__init__.py b/tensorlayer/__init__.py
@@ -25,7 +25,7 @@
 from . import rein
 
 
-__version__ = "1.4.4"
+__version__ = "1.4.5"
 
 global_flag = {}
 global_dict = {}
diff --git a/tensorlayer/layers.py b/tensorlayer/layers.py
@@ -3775,7 +3775,7 @@ def retrieve_seq_length_op2(data):
     return tf.reduce_sum(tf.cast(tf.greater(data, tf.zeros_like(data)), tf.int32), 1)
 
 
-def retrieve_seq_length_op3(data, pad_val=0):
+def retrieve_seq_length_op3(data, pad_val=0): # HangSheng: return tensor for sequence length, if input is tf.string
     data_shape_size = data.get_shape().ndims
     if data_shape_size == 3:
         return tf.reduce_sum(tf.cast(tf.reduce_any(tf.not_equal(data, pad_val), axis=2), dtype=tf.int32), 1)
@@ -3787,7 +3787,7 @@ def retrieve_seq_length_op3(data, pad_val=0):
         raise ValueError("retrieve_seq_length_op3: handling data_shape_size %s hasn't been implemented!" % (data_shape_size))
 
 
-def target_mask_op(data, pad_val=0):
+def target_mask_op(data, pad_val=0):        # HangSheng: return tensor for mask,if input is tf.string
     data_shape_size = data.get_shape().ndims
     if data_shape_size == 3:
         return tf.cast(tf.reduce_any(tf.not_equal(data, pad_val), axis=2), dtype=tf.int32)