UNetTemporalAttentionMultiply
_for_testing/attention_experimentsExperimental
UNetTemporalAttentionMultiplyExperimental: This node is experimental and its behavior may change without notice.
Example
JSON Example
{
"class_type": "UNetTemporalAttentionMultiply",
"inputs": {
"model": [
"node_id",
0
],
"self_structural": 1,
"self_temporal": 1,
"cross_structural": 1,
"cross_temporal": 1
}
}This example shows required inputs only. Connection values like ["node_id", 0] should reference actual node IDs from your workflow.
Inputs
| Name | Type | Status | Constraints | Default |
|---|---|---|---|---|
model | MODEL | required | - | - |
self_structural | FLOAT | required | min: 0, max: 10, step: 0.01 | 1 |
self_temporal | FLOAT | required | min: 0, max: 10, step: 0.01 | 1 |
cross_structural | FLOAT | required | min: 0, max: 10, step: 0.01 | 1 |
cross_temporal | FLOAT | required | min: 0, max: 10, step: 0.01 | 1 |
Outputs
| Index | Name | Type | Is List | Connection Reference |
|---|---|---|---|---|
0 | MODEL | MODEL | No | ["{node_id}", 0] |
How to connect to these outputs
To connect another node's input to an output from this node, use the connection reference format:
["node_id", output_index]Where node_id is the ID of this UNetTemporalAttentionMultiply node in your workflow, and output_index is the index from the table above.
Example
If this node has ID "5" in your workflow:
MODEL (MODEL):["5", 0]
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