Batch Normalization
- class e3nn.nn.BatchNorm(irreps, eps=1e-05, momentum=0.1, affine=True, reduce='mean', instance=False, normalization='component')[source]
Bases:
torch.nn.modules.module.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)[source]
evaluate
- Parameters
input (
torch.Tensor
) – tensor of shape(batch, ..., irreps.dim)
- Returns
tensor of shape
(batch, ..., irreps.dim)
- Return type