models.modules.Up# class Up(scale: int = 2, mode: str = 'nearest')[source]# Bases: LayerGen Upsample layer generator Uses torch.nn.Upsample module. Parameters: scale (int, optional) – Multiplier for spatial size. Defaults to 2. mode (str, optional) – The upsampling algorithm: one of ‘nearest’, ‘linear’, ‘bilinear’, ‘bicubic’ and ‘trilinear’. Defaults to “nearest”. Methods get Initializes and returns the network layer get(in_channels: int) → Tuple[Module, int][source]# Initializes and returns the network layer Parameters: in_channels (int) – Number of input channels. Returns: The generated module and the number of channels that will be after applying this layer to a tensor with in_channels channels. Return type: Tuple[nn.Module, int]