nip.utils.torch.UpsampleSimulateBatchDims

class nip.utils.torch.UpsampleSimulateBatchDims(size: int | Tuple[int, ...] | None = None, scale_factor: float | Tuple[float, ...] | None = None, mode: str = 'nearest', align_corners: bool | None = None, recompute_scale_factor: bool | None = None)

Upsample layer with arbitrary batch dimensions.

See torch.nn.Upsample for documentation.

Assumes an input of shape (… channels height width).

Methods Summary

forward(x)

Apply the module to the input tensor, simulating multiple batch dimensions.

Attributes

T_destination
call_super_init
dump_patches
feature_dims
name
size
scale_factor
mode
align_corners
recompute_scale_factor
training

Methods

forward(x: Tensor) → Tensor

Apply the module to the input tensor, simulating multiple batch dimensions.

Parameters:

x (Tensor) – The input tensor.

Returns:

out (Tensor) – The output tensor after applying the module.