commit
3a955eb32d
@ -67,7 +67,7 @@ NUM_EPOCHS_PER_DECAY = 350.0 # Epochs after which learning rate decays.
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LEARNING_RATE_DECAY_FACTOR = 0.1 # Learning rate decay factor.
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INITIAL_LEARNING_RATE = 0.1 # Initial learning rate.
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# If a model is trained with multiple GPU's prefix all Op names with tower_name
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# If a model is trained with multiple GPUs, prefix all Op names with tower_name
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# to differentiate the operations. Note that this prefix is removed from the
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# names of the summaries when visualizing a model.
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TOWER_NAME = 'tower'
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@ -255,7 +255,7 @@ def inference(images):
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def loss(logits, labels):
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"""Add L2Loss to all the trainable variables.
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Add summary for for "Loss" and "Loss/avg".
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Add summary for "Loss" and "Loss/avg".
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Args:
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logits: Logits from inference().
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labels: Labels from distorted_inputs or inputs(). 1-D tensor
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@ -172,7 +172,7 @@ def distorted_inputs(data_dir, batch_size):
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distorted_image = tf.image.random_flip_left_right(distorted_image)
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# Because these operations are not commutative, consider randomizing
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# randomize the order their operation.
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# the order their operation.
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distorted_image = tf.image.random_brightness(distorted_image,
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max_delta=63)
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distorted_image = tf.image.random_contrast(distorted_image,
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