Cleaning & commenting #2 - updating comments & docstrings

Edmond Yoo

2018-10-13 c59db54775606349f6ba5c6cab7fcb34498bb31d

 cfg/go.test.cfg

@@ -3,102 +3,126 @@
subdivisions=1
height=19
width=19
channels=8
channels=1
momentum=0.9
decay=0.0005

learning_rate=0.1
max_batches = 0
policy=steps
steps=50000
scales=.1
policy=poly
power=4
max_batches=400000

[convolutional]
filters=512
filters=192
size=3
stride=1
pad=1
activation=leaky
activation=relu
batch_normalize=1

[convolutional]
filters=256
size=1
stride=1
pad=1
activation=leaky
batch_normalize=1

[convolutional]
filters=512
filters=192
size=3
stride=1
pad=1
activation=leaky
activation=relu
batch_normalize=1

[convolutional]
filters=256
size=1
stride=1
pad=1
activation=leaky
batch_normalize=1

[convolutional]
filters=512
filters=192
size=3
stride=1
pad=1
activation=leaky
activation=relu
batch_normalize=1

[convolutional]
filters=256
size=1
stride=1
pad=1
activation=leaky
batch_normalize=1

[convolutional]
filters=512
filters=192
size=3
stride=1
pad=1
activation=leaky
activation=relu
batch_normalize=1

[convolutional]
filters=256
size=1
stride=1
pad=1
activation=leaky
batch_normalize=1

[convolutional]
filters=512
filters=192
size=3
stride=1
pad=1
activation=leaky
activation=relu
batch_normalize=1

[convolutional]
filters=256
size=1
filters=192
size=3
stride=1
pad=1
activation=leaky
activation=relu
batch_normalize=1

[convolutional]
filters=192
size=3
stride=1
pad=1
activation=relu
batch_normalize=1

[convolutional]
filters=192
size=3
stride=1
pad=1
activation=relu
batch_normalize=1

[convolutional]
filters=192
size=3
stride=1
pad=1
activation=relu
batch_normalize=1

[convolutional]
filters=192
size=3
stride=1
pad=1
activation=relu
batch_normalize=1

[convolutional]
filters=192
size=3
stride=1
pad=1
activation=relu
batch_normalize=1

[convolutional]
filters=192
size=3
stride=1
pad=1
activation=relu
batch_normalize=1

[convolutional]
filters=192
size=3
stride=1
pad=1
activation=relu
batch_normalize=1


[convolutional]
filters=1
size=1
stride=1
pad=1
activation=leaky
activation=linear

[softmax]