experiments/STT-tensorflow
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Merge pull request #1469 from izeye/polish-20160312

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Fix typos
This commit is contained in:
Vijay Vasudevan 2016-03-12 11:43:38 -08:00
commit 3a955eb32d
2 changed files with 3 additions and 3 deletions
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4
tensorflow/models/image/cifar10/cifar10.py
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@ -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. LEARNING_RATE_DECAY_FACTOR = 0.1 # Learning rate decay factor.
INITIAL_LEARNING_RATE = 0.1 # Initial learning rate. 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 # to differentiate the operations. Note that this prefix is removed from the
# names of the summaries when visualizing a model. # names of the summaries when visualizing a model.
TOWER_NAME = 'tower' TOWER_NAME = 'tower'
@ -255,7 +255,7 @@ def inference(images):
def loss(logits, labels): def loss(logits, labels):
"""Add L2Loss to all the trainable variables. """Add L2Loss to all the trainable variables.
Add summary for for "Loss" and "Loss/avg". Add summary for "Loss" and "Loss/avg".
Args: Args:
logits: Logits from inference(). logits: Logits from inference().
labels: Labels from distorted_inputs or inputs(). 1-D tensor labels: Labels from distorted_inputs or inputs(). 1-D tensor

2
tensorflow/models/image/cifar10/cifar10_input.py
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@ -172,7 +172,7 @@ def distorted_inputs(data_dir, batch_size):
distorted_image = tf.image.random_flip_left_right(distorted_image) distorted_image = tf.image.random_flip_left_right(distorted_image)
# Because these operations are not commutative, consider randomizing # 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, distorted_image = tf.image.random_brightness(distorted_image,
max_delta=63) max_delta=63)
distorted_image = tf.image.random_contrast(distorted_image, distorted_image = tf.image.random_contrast(distorted_image,