Method __init__

monai/networks/nets/flexible_unet.py:191–216

(
        self,
        spatial_dims: int,
        in_channels: int,
        out_channels: int,
        kernel_size: int = 3,
        act: tuple | str | None = None,
        scale_factor: float = 1.0,
    )

    """

    def __init__(
        self,
        spatial_dims: int,
        in_channels: int,
        out_channels: int,
        kernel_size: int = 3,
        act: tuple | str | None = None,
        scale_factor: float = 1.0,
    ):
        conv_layer = Conv[Conv.CONV, spatial_dims](
            in_channels=in_channels, out_channels=out_channels, kernel_size=kernel_size, padding=kernel_size // 2
        )
        up_layer: nn.Module = nn.Identity()
        if scale_factor > 1.0:
            up_layer = UpSample(
                spatial_dims=spatial_dims,
                scale_factor=scale_factor,
                mode="nontrainable",
                pre_conv=None,
                interp_mode=InterpolateMode.LINEAR,
            )
        if act is not None:
            act_layer = get_act_layer(act)
        else:
            act_layer = nn.Identity()
        super().__init__(conv_layer, up_layer, act_layer)


class FlexibleUNet(nn.Module):