UBlock

class torchelie.nn.UBlock(in_channels: int, hidden_channels: int, inner: torch.nn.modules.module.Module)

condition(z: torch.Tensor) → None

forward(x_orig: torch.Tensor, z: Optional[torch.Tensor] = None) → torch.Tensor

leaky() → torchelie.nn.encdec.UBlock

remove_batchnorm() → torchelie.nn.encdec.UBlock

remove_upsampling_conv() → torchelie.nn.encdec.UBlock

set_decoder_num_layers(num_layers: int) → torchelie.nn.encdec.UBlock

set_encoder_num_layers(num_layers: int) → torchelie.nn.encdec.UBlock

set_padding_mode(mode: str) → torchelie.nn.encdec.UBlock

to_bilinear_sampling() → torchelie.nn.encdec.UBlock

downsample: torch.nn.modules.module.Module