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code/unet/train_unet.py

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@@ -386,7 +386,7 @@ def main():
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parser.add_argument('-batch_size',
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type=int,
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nargs='+',
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default=[5, 1, 1],
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default=[5, 5, 1],
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help='Batch size [train, val, test]')
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parser.add_argument('-data_augmentation',
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type=dict,

doc/unet.txt

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@@ -156,6 +156,14 @@ And finally the output path (to obtain *number of classes* feature maps):
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:start-after: start-snippet-output
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:end-before: end-snippet-output
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Running ``train_unet.py`` on a Titan X lasted for around 60 minutes, ending with the following:
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.. code-block:: text
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$ THEANO_FLAGS=device=cuda0,floatX=float32,dnn.conv.algo_fwd=time_once,dnn.conv.algo_bwd_data=time_once,dnn.conv.algo_bwd_filter=time_once,gpuarray.preallocate=1 python train_unet.py
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[...]
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EPOCH 364: Avg epoch training cost train 0.160667, cost val 0.265909, acc val 0.888796, jacc val class 0 0.636058, jacc val class 1 0.861970, jacc val 0.749014 took 4.379772 s
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References
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