def create_linear_transform():
if args.linear_type == 'lu':
return transforms.CompositeTransform([
transforms.RandomPermutation(args.latent_features),
transforms.LULinear(args.latent_features, identity_init=True)
])
elif args.linear_type == 'svd':
return transforms.SVDLinear(args.latent_features,
num_householder=4,
identity_init=True)
elif args.linear_type == 'perm':
return transforms.RandomPermutation(args.latent_features)
else:
raise ValueError
def create_linear_transform():
linear_transform = transforms.CompositeTransform(
[transforms.RandomPermutation(features=feature_dim)])
return linear_transform
def __init__(self, num_channels, using_cache=False, identity_init=True):
super().__init__(num_channels, using_cache, identity_init)
self.permutation = transforms.RandomPermutation(num_channels, dim=1)
