Batch Normalization
- class e3nn.nn.BatchNorm(irreps: Irreps, eps: float = 1e-05, momentum: float = 0.1, affine: bool = True, reduce: str = 'mean', instance: bool = False, normalization: str = 'component')[source]
Bases:
Module
Batch normalization for orthonormal representations
It normalizes by the norm of the representations. Note that the norm is invariant only for orthonormal representations. Irreducible representations
wigner_D
are orthonormal.- Parameters:
irreps (
o3.Irreps
) – representationeps (float) – avoid division by zero when we normalize by the variance
momentum (float) – momentum of the running average
affine (bool) – do we have weight and bias parameters
reduce ({'mean', 'max'}) – method used to reduce
instance (bool) – apply instance norm instead of batch norm
Methods:
forward
(input)evaluate
- forward(input) Tensor [source]
evaluate
- Parameters:
input (
torch.Tensor
) – tensor of shape(batch, ..., irreps.dim)
- Returns:
tensor of shape
(batch, ..., irreps.dim)
- Return type: