nip.utils.torch.BatchNorm1dSimulateBatchDims

nip.utils.torch.BatchNorm1dSimulateBatchDims#

class nip.utils.torch.BatchNorm1dSimulateBatchDims(num_features: int, eps: float = 1e-05, momentum: float = 0.1, affine: bool = True, track_running_stats: bool = True, device=None, dtype=None)[source]#

Batch normalization layer with arbitrary batch dimensions.

See torch.nn.BatchNorm1d for documentation.

Assumes an input of shape (… features).

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

num_features

eps

momentum

affine

track_running_stats

training

Methods

forward(x: Tensor) Tensor[source]#

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.