Merge changes from github.

PiperOrigin-RevId: 155709893

7 files changed, 7 insertions, 7 deletions

diff --git a/tensorflow/contrib/keras/python/keras/datasets/imdb.py b/tensorflow/contrib/keras/python/keras/datasets/imdb.py
index bafd92aca6..5c087fe63f 100644
--- a/tensorflow/contrib/keras/python/keras/datasets/imdb.py
+++ b/tensorflow/contrib/keras/python/keras/datasets/imdb.py
@@ -41,7 +41,7 @@ def load_data(path='imdb.npz',
       num_words: max number of words to include. Words are ranked
           by how often they occur (in the training set) and only
           the most frequent words are kept
-      skip_top: skip the top N most frequently occuring words
+      skip_top: skip the top N most frequently occurring words
           (which may not be informative).
       maxlen: truncate sequences after this length.
       seed: random seed for sample shuffling.
diff --git a/tensorflow/contrib/keras/python/keras/datasets/reuters.py b/tensorflow/contrib/keras/python/keras/datasets/reuters.py
index 81e940a846..b1c22fee63 100644
--- a/tensorflow/contrib/keras/python/keras/datasets/reuters.py
+++ b/tensorflow/contrib/keras/python/keras/datasets/reuters.py
@@ -43,7 +43,7 @@ def load_data(path='reuters.npz',
       num_words: max number of words to include. Words are ranked
           by how often they occur (in the training set) and only
           the most frequent words are kept
-      skip_top: skip the top N most frequently occuring words
+      skip_top: skip the top N most frequently occurring words
           (which may not be informative).
       maxlen: truncate sequences after this length.
       test_split: Fraction of the dataset to be used as test data.
diff --git a/tensorflow/contrib/keras/python/keras/engine/topology.py b/tensorflow/contrib/keras/python/keras/engine/topology.py
index 0336fc4bf4..3d9ed51a1c 100644
--- a/tensorflow/contrib/keras/python/keras/engine/topology.py
+++ b/tensorflow/contrib/keras/python/keras/engine/topology.py
@@ -649,7 +649,7 @@ class Layer(tf_base_layers.Layer):
                           'but was passed an input_mask: ' + str(mask))
       # masking not explicitly supported: return None as mask
       return None
-    # if masking is explictly supported, by default
+    # if masking is explicitly supported, by default
     # carry over the input mask
     return mask
 
diff --git a/tensorflow/contrib/keras/python/keras/engine/training.py b/tensorflow/contrib/keras/python/keras/engine/training.py
index ba6201713e..96d1c2f262 100644
--- a/tensorflow/contrib/keras/python/keras/engine/training.py
+++ b/tensorflow/contrib/keras/python/keras/engine/training.py
@@ -245,7 +245,7 @@ def _check_array_lengths(inputs, targets, weights):
 
 
 def _check_loss_and_target_compatibility(targets, loss_fns, output_shapes):
-  """Does validation on the compatiblity of targets and loss functions.
+  """Does validation on the compatibility of targets and loss functions.
 
   This helps prevent users from using loss functions incorrectly.
 
diff --git a/tensorflow/contrib/keras/python/keras/layers/normalization.py b/tensorflow/contrib/keras/python/keras/layers/normalization.py
index df77401aee..ea229fdce1 100644
--- a/tensorflow/contrib/keras/python/keras/layers/normalization.py
+++ b/tensorflow/contrib/keras/python/keras/layers/normalization.py
@@ -169,7 +169,7 @@ class BatchNormalization(Layer):
 
       def normalize_inference():
         if needs_broadcasting:
-          # In this case we must explictly broadcast all parameters.
+          # In this case we must explicitly broadcast all parameters.
           broadcast_moving_mean = K.reshape(self.moving_mean, broadcast_shape)
           broadcast_moving_variance = K.reshape(self.moving_variance,
                                                 broadcast_shape)
diff --git a/tensorflow/contrib/keras/python/keras/models.py b/tensorflow/contrib/keras/python/keras/models.py
index 52456a4bb5..1c041091fc 100644
--- a/tensorflow/contrib/keras/python/keras/models.py
+++ b/tensorflow/contrib/keras/python/keras/models.py
@@ -221,7 +221,7 @@ def load_model(filepath, custom_objects=None):
         obj: object, dict, or list.
 
     Returns:
-        The same structure, where occurences
+        The same structure, where occurrences
             of a custom object name have been replaced
             with the custom object.
     """
diff --git a/tensorflow/contrib/keras/python/keras/preprocessing/sequence.py b/tensorflow/contrib/keras/python/keras/preprocessing/sequence.py
index 5a24a63b01..692a359ead 100644
--- a/tensorflow/contrib/keras/python/keras/preprocessing/sequence.py
+++ b/tensorflow/contrib/keras/python/keras/preprocessing/sequence.py
@@ -156,7 +156,7 @@ def skipgrams(sequence,
           of word indices (integers). If using a `sampling_table`,
           word indices are expected to match the rank
           of the words in a reference dataset (e.g. 10 would encode
-          the 10-th most frequently occuring token).
+          the 10-th most frequently occurring token).
           Note that index 0 is expected to be a non-word and will be skipped.
       vocabulary_size: int. maximum possible word index + 1
       window_size: int. actually half-window.