Fix typos (keras-team#5753)

lemonhall · Mar 15, 2017 · 0cc52cf · 0cc52cf
1 parent 36e526e
commit 0cc52cf
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Showing 4 changed files with 6 additions and 6 deletions.
diff --git a/keras/backend/tensorflow_backend.py b/keras/backend/tensorflow_backend.py
@@ -630,7 +630,7 @@ def random_uniform_variable(shape, low, high, dtype=None,
 
     # Arguments
         shape: Tuple of integers, shape of returned Keras variable.
-        low: Float, lower boundary of the output inteval.
+        low: Float, lower boundary of the output interval.
         high: Float, upper boundary of the output interval.
         dtype: String, dtype of returned Keras variable.
         name: String, name of returned Keras variable.
@@ -1906,7 +1906,7 @@ def one_hot(indices, num_classes):
 
 
 def reverse(x, axes):
-    """Reverse a tensor along the the specified axes.
+    """Reverse a tensor along the specified axes.
 
     # Arguments
         x: Tensor to reverse.
@@ -3153,7 +3153,7 @@ def random_binomial(shape, p=0.0, dtype=None, seed=None):
 
     # Arguments
         shape: A tuple of integers, the shape of tensor to create.
-        p: A float, `0. <= p <= 1`, probability of binomlai distribution.
+        p: A float, `0. <= p <= 1`, probability of binomial distribution.
         dtype: String, dtype of returned tensor.
         seed: Integer, random seed.
 

diff --git a/keras/backend/theano_backend.py b/keras/backend/theano_backend.py
@@ -1002,7 +1002,7 @@ def one_hot(indices, num_classes):
 
 
 def reverse(x, axes):
-    """Reverse a tensor along the the specified axes
+    """Reverse a tensor along the specified axes
     """
     if isinstance(axes, int):
         axes = [axes]

diff --git a/keras/engine/training.py b/keras/engine/training.py
@@ -1594,7 +1594,7 @@ def train_on_batch(self, x, y,
                 In this case you should make sure to specify
                 sample_weight_mode="temporal" in compile().
             class_weight: optional dictionary mapping
-                lass indices (integers) to
+                class indices (integers) to
                 a weight (float) to apply to the model's loss for the samples
                 from this class during training.
                 This can be useful to tell the model to "pay more attention" to

diff --git a/keras/layers/core.py b/keras/layers/core.py
@@ -27,7 +27,7 @@ class Masking(Layer):
 
     For each timestep in the input tensor (dimension #1 in the tensor),
     if all values in the input tensor at that timestep
-    are equal to `mask_value`, then the timestep will masked (skipped)
+    are equal to `mask_value`, then the timestep will be masked (skipped)
     in all downstream layers (as long as they support masking).
 
     If any downstream layer does not support masking yet receives such