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# UNetTemporalAttentionMultiply - ComfyUI Built-in Node Documentation

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

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/UNetTemporalAttentionMultiply/en.md)

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 |