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Switch default to small model to reduce memory usage.
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enhance.py

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@@ -37,6 +37,7 @@
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add_arg('files', nargs='*', default=[])
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add_arg('--scales', default=2, type=int, help='How many times to perform 2x upsampling.')
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add_arg('--model', default='medium', type=str, help='Name of the neural network to load/save.')
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add_arg('--model', default='small', type=str, help='Name of the neural network to load/save.')
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add_arg('--train', default=False, type=str, help='File pattern to load for training.')
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add_arg('--batch-resolution', default=192, type=int, help='Resolution of images in training batch.')
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add_arg('--batch-size', default=15, type=int, help='Number of images per training batch.')

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