def senet154(num_classes=1000, pretrained='imagenet', first_stride=1):
model = SENet(senet.SEBottleneck, [3, 8, 36, 3],
groups=64,
reduction=16,
first_stride=first_stride,
dropout_p=0.2,
num_classes=num_classes)
if pretrained is not None:
settings = senet.pretrained_settings['senet154'][pretrained]
senet.initialize_pretrained_model(model, num_classes, settings)
return model
def se_resnet101(num_classes=1000, pretrained='imagenet', first_stride=1):
model = SENet(senet.SEBottleneck, [3, 4, 23, 3],
groups=1,
reduction=16,
first_stride=first_stride,
dropout_p=None,
inplanes=64,
input_3x3=False,
downsample_kernel_size=1,
downsample_padding=0,
num_classes=num_classes)
if pretrained is not None:
settings = senet.pretrained_settings['se_resnet101'][pretrained]
senet.initialize_pretrained_model(model, num_classes, settings)
return model