Merge branch 'master' of https://github.com/zsdonghao/tensorlayer

Author: zsdonghao

tensorlayer/cost.py

@@ -76,7 +76,7 @@ def binary_cross_entropy(output, target, epsilon=1e-8, name='bce_loss'):
 
 
 def mean_squared_error(output, target, is_mean=False):
-    """Return the TensorFlow expression of mean-squre-error of two distributions.
+    """Return the TensorFlow expression of mean-square-error of two distributions.
 
     Parameters
     ----------
@@ -102,7 +102,7 @@ def mean_squared_error(output, target, is_mean=False):
         return mse
 
 def normalized_mean_square_error(output, target):
-    """Return the TensorFlow expression of normalized mean-squre-error of two distributions.
+    """Return the TensorFlow expression of normalized mean-square-error of two distributions.
 
     Parameters
     ----------

tensorlayer/layers.py

@@ -778,7 +778,7 @@ def __init__(
         print("     lambda_l2_w: %f" % lambda_l2_w)
         print("     learning_rate: %f" % learning_rate)
 
-        # Mean-squre-error i.e. quadratic-cost
+        # Mean-square-error i.e. quadratic-cost
         mse = tf.reduce_sum(tf.squared_difference(y, x_recon),  1)
         mse = tf.reduce_mean(mse)            # in theano: mse = ((y - x) ** 2 ).sum(axis=1).mean()
             # mse = tf.reduce_mean(tf.reduce_sum(tf.square(tf.sub(y, x_recon)),  1))