This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! Edit on GitHubThe LatentCutToBatch node takes a latent representation and splits it along a specified dimension into multiple slices. These slices are then stacked into a new batch dimension, effectively converting a single latent sample into a batch of smaller latent samples. This is useful for processing different parts of a latent space independently.
Inputs
| Parameter | Data Type | Required | Range | Description |
|---|---|---|---|---|
samples | LATENT | Yes | - | The latent representation to be split and batched. |
dim | COMBO | Yes | "t""x""y" | The dimension along which to cut the latent samples. "t" refers to the temporal dimension, "x" to the width, and "y" to the height. |
slice_size | INT | Yes | 1 to 16384 | The size of each slice to cut from the specified dimension. If the dimension’s size is not perfectly divisible by this value, the remainder is discarded. (default: 1) |
Outputs
| Output Name | Data Type | Description |
|---|---|---|
samples | LATENT | The resulting latent batch, containing the sliced and stacked samples. |