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Normalization layers
Customized normalization layers for supporting various models in 🤗 Diffusers.
AdaLayerNorm
class diffusers.models.normalization.AdaLayerNorm
< source >( embedding_dim: int num_embeddings: int )
Norm layer modified to incorporate timestep embeddings.
AdaLayerNormZero
class diffusers.models.normalization.AdaLayerNormZero
< source >( embedding_dim: int num_embeddings: int )
Norm layer adaptive layer norm zero (adaLN-Zero).
AdaLayerNormSingle
class diffusers.models.normalization.AdaLayerNormSingle
< source >( embedding_dim: int use_additional_conditions: bool = False )
Norm layer adaptive layer norm single (adaLN-single).
As proposed in PixArt-Alpha (see: https://arxiv.org/abs/2310.00426; Section 2.3).
AdaGroupNorm
class diffusers.models.normalization.AdaGroupNorm
< source >( embedding_dim: int out_dim: int num_groups: int act_fn: Optional = None eps: float = 1e-05 )
Parameters
- embedding_dim (
int
) — The size of each embedding vector. - num_embeddings (
int
) — The size of the embeddings dictionary. - num_groups (
int
) — The number of groups to separate the channels into. - act_fn (
str
, optional, defaults toNone
) — The activation function to use. - eps (
float
, optional, defaults to1e-5
) — The epsilon value to use for numerical stability.
GroupNorm layer modified to incorporate timestep embeddings.