IPAdapterAttnProcessor  
Attention processor for Multiple IP-Adapters.  
Args:
hidden_size (`int`):
The hidden size of the attention layer.
cross_attention_dim (`int`):
The number of channels in the `encoder_hidden_states`.
num_tokens (`int`, `Tuple[int]` or `List[int]`, defaults to `(4,)`):
The context length of the image features.
scale (`float` or List[`float`], defaults to 1.0):
the weight scale of image prompt.  
IPAdapterAttnProcessor  
Attention processor for Multiple IP-Adapters.  
Args:
hidden_size (`int`):
The hidden size of the attention layer.
cross_attention_dim (`int`):
The number of channels in the `encoder_hidden_states`.
num_tokens (`int`, `Tuple[int]` or `List[int]`, defaults to `(4,)`):
The context length of the image features.
scale (`float` or List[`float`], defaults to 1.0):
the weight scale of image prompt.
2_0  
SD3IPAdapterJointAttnProcessor2_0  
Attention processor for IP-Adapter used typically in processing the SD3-like self-attention projections, with
additional image-based information and timestep embeddings.  
Args:
hidden_size (`int`):
The number of hidden channels.
ip_hidden_states_dim (`int`):
The image feature dimension.
head_dim (`int`):
The number of head channels.
timesteps_emb_dim (`int`, defaults to 1280):
The number of input channels for timestep embedding.
scale (`float`, defaults to 0.5):
IP-Adapter scale.
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/attnprocessor.md