diff --git a/tensorflow/models/image/cifar10/cifar10.py b/tensorflow/models/image/cifar10/cifar10.py
index 8f5fd4f50d1..05c8e70f5fc 100644
--- a/tensorflow/models/image/cifar10/cifar10.py
+++ b/tensorflow/models/image/cifar10/cifar10.py
@@ -67,7 +67,7 @@ NUM_EPOCHS_PER_DECAY = 350.0      # Epochs after which learning rate decays.
 LEARNING_RATE_DECAY_FACTOR = 0.1  # Learning rate decay factor.
 INITIAL_LEARNING_RATE = 0.1       # Initial learning rate.
 
-# If a model is trained with multiple GPU's prefix all Op names with tower_name
+# If a model is trained with multiple GPUs, prefix all Op names with tower_name
 # to differentiate the operations. Note that this prefix is removed from the
 # names of the summaries when visualizing a model.
 TOWER_NAME = 'tower'
@@ -255,7 +255,7 @@ def inference(images):
 def loss(logits, labels):
   """Add L2Loss to all the trainable variables.
 
-  Add summary for for "Loss" and "Loss/avg".
+  Add summary for "Loss" and "Loss/avg".
   Args:
     logits: Logits from inference().
     labels: Labels from distorted_inputs or inputs(). 1-D tensor
diff --git a/tensorflow/models/image/cifar10/cifar10_input.py b/tensorflow/models/image/cifar10/cifar10_input.py
index a9a086992dc..0d48a3549ce 100644
--- a/tensorflow/models/image/cifar10/cifar10_input.py
+++ b/tensorflow/models/image/cifar10/cifar10_input.py
@@ -172,7 +172,7 @@ def distorted_inputs(data_dir, batch_size):
   distorted_image = tf.image.random_flip_left_right(distorted_image)
 
   # Because these operations are not commutative, consider randomizing
-  # randomize the order their operation.
+  # the order their operation.
   distorted_image = tf.image.random_brightness(distorted_image,
                                                max_delta=63)
   distorted_image = tf.image.random_contrast(distorted_image,