UNetTemporalAttentionMultiply - ComfyUI Built-in Node Documentation

Complete documentation for the UNetTemporalAttentionMultiply node in ComfyUI. Learn its inputs, outputs, parameters and usage.

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The UNetTemporalAttentionMultiply node applies multiplication factors to different types of attention mechanisms in a temporal UNet model. It modifies the model by adjusting the weights of self-attention and cross-attention layers, distinguishing between structural and temporal components. This allows fine-tuning of how much influence each attention type has on the model’s output.

Inputs

Parameter	Data Type	Required	Range	Description
model	MODEL	Yes	-	The input model to modify with attention multipliers
self_structural	FLOAT	No	0.0 - 10.0	Multiplier for self-attention structural components (default: 1.0)
self_temporal	FLOAT	No	0.0 - 10.0	Multiplier for self-attention temporal components (default: 1.0)
cross_structural	FLOAT	No	0.0 - 10.0	Multiplier for cross-attention structural components (default: 1.0)
cross_temporal	FLOAT	No	0.0 - 10.0	Multiplier for cross-attention temporal components (default: 1.0)

Outputs

Output Name	Data Type	Description
model	MODEL	The modified model with adjusted attention weights