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# CosineDPMSolverMultistepScheduler
The [CosineDPMSolverMultistepScheduler](/docs/diffusers/pr_14404/en/api/schedulers/cosine_dpm#diffusers.CosineDPMSolverMultistepScheduler) is a variant of [DPMSolverMultistepScheduler](/docs/diffusers/pr_14404/en/api/schedulers/multistep_dpm_solver#diffusers.DPMSolverMultistepScheduler) with cosine schedule, proposed by Nichol and Dhariwal (2021).
It is being used in the [Stable Audio Open](https://huggingface.co/papers/2407.14358) paper and the [Stability-AI/stable-audio-tool](https://github.com/Stability-AI/stable-audio-tools) codebase.
This scheduler was contributed by [Yoach Lacombe](https://huggingface.co/ylacombe).
## CosineDPMSolverMultistepScheduler[[diffusers.CosineDPMSolverMultistepScheduler]]
#### diffusers.CosineDPMSolverMultistepScheduler[[diffusers.CosineDPMSolverMultistepScheduler]]
```python
diffusers.CosineDPMSolverMultistepScheduler(*args, **kwargs)
```
[Source](https://github.com/huggingface/diffusers/blob/vr_14404/src/diffusers/utils/dummy_torch_and_torchsde_objects.py#L5)
## 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)
```
[Source](https://github.com/huggingface/diffusers/blob/vr_14404/src/diffusers/schedulers/scheduling_utils.py#L66)
**Parameters:**
prev_sample (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` for images) : Computed sample `(x_{t-1})` of previous timestep. `prev_sample` should be used as next model input in the denoising loop.
Base class for the output of a scheduler's `step` function.

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