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author | 2016-03-15 18:45:27 -0800 | |
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committer | 2016-03-16 16:20:04 -0700 | |
commit | 9a4878cc17d4039939e8df5a2a984cca8028baeb (patch) | |
tree | d58e341fe594a245a24539c8c37e61d67dcd93e2 /tensorflow/models | |
parent | fdc6752cda33e8d5879e4db68093eca7d7395988 (diff) |
Rollback of: "Merge changes from github."
Change: 117304114
Diffstat (limited to 'tensorflow/models')
-rw-r--r-- | tensorflow/models/image/cifar10/cifar10.py | 4 | ||||
-rw-r--r-- | tensorflow/models/image/cifar10/cifar10_input.py | 2 |
2 files changed, 3 insertions, 3 deletions
diff --git a/tensorflow/models/image/cifar10/cifar10.py b/tensorflow/models/image/cifar10/cifar10.py index 05c8e70f5f..8f5fd4f50d 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 GPUs, prefix all Op names with tower_name +# If a model is trained with multiple GPU's 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 "Loss" and "Loss/avg". + Add summary for 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 0d48a3549c..a9a086992d 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 - # the order their operation. + # randomize the order their operation. distorted_image = tf.image.random_brightness(distorted_image, max_delta=63) distorted_image = tf.image.random_contrast(distorted_image, |