# DPMSolverSDEScheduler

The `DPMSolverSDEScheduler` is inspired by the stochastic sampler from the [Elucidating the Design Space of Diffusion-Based Generative Models](https://huggingface.co/papers/2206.00364) paper, and the scheduler is ported from and created by [Katherine Crowson](https://github.com/crowsonkb/).

## DPMSolverSDEScheduler[[diffusers.DPMSolverSDEScheduler]]

#### diffusers.DPMSolverSDEScheduler[[diffusers.DPMSolverSDEScheduler]]

```python
diffusers.DPMSolverSDEScheduler(*args, **kwargs)
```

[소스](https://github.com/huggingface/diffusers/blob/main/src/diffusers/utils/dummy_torch_and_torchsde_objects.py#L20)

## SchedulerOutput[[diffusers.schedulers.scheduling_utils.SchedulerOutput]]

#### diffusers.schedulers.scheduling_utils.SchedulerOutput[[diffusers.schedulers.scheduling_utils.SchedulerOutput]]

```python
diffusers.schedulers.scheduling_utils.SchedulerOutput(prev_sample: Tensor)
```

[소스](https://github.com/huggingface/diffusers/blob/main/src/diffusers/schedulers/scheduling_utils.py#L66)

**매개변수:**

prev_sample (`torch.Tensor`, 이미지인 경우 shape는 `(batch_size, num_channels, height, width)`) : 이전 timestep의 계산된 샘플 `(x_{t-1})`. `prev_sample`은 denoising 루프에서 다음 모델 입력으로 사용해야 합니다.

스케줄러의 `step` 함수 출력을 위한 베이스 클래스.