added output layers for bi-rnn encoder

Former-commit-id: 419db5d
asyml · May 30, 2018 · 77c08db · 77c08db
1 parent ebec93d
commit 77c08db
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Showing 4 changed files with 375 additions and 64 deletions.
diff --git a/texar/modules/connectors/connectors.py b/texar/modules/connectors/connectors.py
@@ -414,9 +414,9 @@ class which inherits
                 to generate. `None` is required in training stage.
 
         Returns:
-            output: If `num_samples`==None, returns a Tensor of shape 
-                `[batch_size x output_size]`, else returns a Tensor of shape 
-                `[num_samples x output_size]`. `num_samples` should be specified 
+            output: If `num_samples`==None, returns a Tensor of shape
+                `[batch_size x output_size]`, else returns a Tensor of shape
+                `[num_samples x output_size]`. `num_samples` should be specified
                 if not in training stage.
             latent_z: The latent sampled z
 
@@ -644,7 +644,7 @@ def _build(self, connector_inputs, transform=True):
 
         Args:
             connector_inputs: a list of connector states
-            transform: If ``True``, then the output are automatically 
+            transform: If `True`, then the output are automatically
                 transformed to match :attr:`output_size`.
 
         Returns:

diff --git a/texar/modules/decoders/rnn_decoders.py b/texar/modules/decoders/rnn_decoders.py
@@ -355,7 +355,7 @@ def default_hparams():
             Here:
 
             "attention" : dict
-                A dictionary of attention hyperparameters, which includes:
+                Attention hyperparameters, which includes:
 
                 "type" : str
                     Name or full path to the attention class which can be