def build_model():
model = Flowavenet(in_channel=1,
cin_channel=args.cin_channels,
n_block=args.n_block,
n_flow=args.n_flow,
n_layer=args.n_layer,
affine=True,
pretrained=True,
block_per_split=args.block_per_split)
return model
def build_model():
pretrained = True if args.load_step > 0 else False
model = Flowavenet(in_channel=1,
cin_channel=args.cin_channels,
n_block=args.n_block,
n_flow=args.n_flow,
n_layer=args.n_layer,
affine=True,
pretrained=pretrained,
block_per_split=args.block_per_split)
return model
def build_model():
causality = True if args.causal == 'yes' else False
model = Flowavenet(in_channel=1,
cin_channel=args.cin_channels,
n_block=args.n_block,
n_flow=args.n_flow,
n_layer=args.n_layer,
affine=True,
causal=causality,
pretrained=True)
return model