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resnet10.cfg
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resnet10.cfg
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[net]
# Training
batch=128
subdivisions=1
# Testing
# batch=1
# subdivisions=1
height=256
width=256
channels=3
min_crop=128
max_crop=448
burn_in=1000
learning_rate=0.1
policy=poly
power=4
max_batches=800000
momentum=0.9
decay=0.0005
angle=7
hue=.1
saturation=.75
exposure=.75
aspect=.75
[convolutional]
batch_normalize=1
filters=64
size=7
stride=2
pad=1
activation=leaky
[maxpool]
size=2
stride=2
# Residual Block
[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=linear
[shortcut]
activation=leaky
from=-3
# Strided Residual Block
[convolutional]
batch_normalize=1
filters=128
size=3
stride=2
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=linear
[shortcut]
activation=leaky
from=-3
# Strided Residual Block
[convolutional]
batch_normalize=1
filters=256
size=3
stride=2
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=linear
[shortcut]
activation=leaky
from=-3
# Strided Residual Block
[convolutional]
batch_normalize=1
filters=512
size=3
stride=2
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=linear
[shortcut]
activation=leaky
from=-3
[avgpool]
[convolutional]
filters=1000
size=1
stride=1
pad=1
activation=linear
[softmax]
groups=1