Normalization layers Customized normalization layers for supporting various models in 🤗 Diffusers.  AdaLayerNorm  class diffusers.models.normalization.AdaLayerNorm  < source > ( embedding_dim: int num_embeddings: int  )   Parameters   embedding_dim (int) — The size of each embedding vector.   num_embeddings (int) — The size of the embeddings dictionary.    Norm layer modified to incorporate timestep embeddings.  AdaLayerNormZero  class diffusers.models.normalization.AdaLayerNormZero  < source > ( embedding_dim: int num_embeddings: int  )   Parameters   embedding_dim (int) — The size of each embedding vector.   num_embeddings (int) — The size of the embeddings dictionary.    Norm layer adaptive layer norm zero (adaLN-Zero).  AdaLayerNormSingle  class diffusers.models.normalization.AdaLayerNormSingle  < source > ( embedding_dim: int use_additional_conditions: bool = False  )   Parameters   embedding_dim (int) — The size of each embedding vector.   use_additional_conditions (bool) — To use additional conditions for normalization or not.    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 to None) — The activation function to use.   eps (float, optional, defaults to 1e-5) — The epsilon value to use for numerical stability.    GroupNorm layer modified to incorporate timestep embeddings.