ModulatedConv

class torchelie.nn.ModulatedConv(in_channels: int, noise_channels: int, *args, demodulate: bool = True, gain: float = 1, **kwargs)

condition(z: torch.Tensor) → None

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

to_equal_lr(leak: float = 0.2) → torchelie.nn.layers.ModulatedConv

bias: Optional[torch.Tensor]

dilation: Tuple[int, …]

groups: int

kernel_size: Tuple[int, …]

out_channels: int

output_padding: Tuple[int, …]

padding: Tuple[int, …]

padding_mode: str

stride: Tuple[int, …]

transposed: bool

weight: torch.Tensor