The LaplaceScheduler node generates a sequence of sigma values following a Laplace distribution for use in diffusion sampling. It creates a schedule of noise levels that gradually decrease from a maximum to minimum value, using Laplace distribution parameters to control the progression. This scheduler is commonly used in custom sampling workflows to define the noise schedule for diffusion models.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| --- | --- | --- | --- | --- |
| `steps` | Number of sampling steps in the schedule (default: 20) | INT | Yes | 1 to 10000 |
| `sigma_max` | Maximum sigma value at the start of the schedule (default: 14.614642) | FLOAT | Yes | 0.0 to 5000.0 |
| `sigma_min` | Minimum sigma value at the end of the schedule (default: 0.0291675) | FLOAT | Yes | 0.0 to 5000.0 |
| `mu` | Mean parameter for the Laplace distribution (default: 0.0) | FLOAT | Yes | -10.0 to 10.0 |
| `beta` | Scale parameter for the Laplace distribution (default: 0.5) | FLOAT | Yes | 0.0 to 10.0 |

## Outputs

| Output Name | Description | Data Type |
| --- | --- | --- |
| `SIGMAS` | A sequence of sigma values following a Laplace distribution schedule | SIGMAS |

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