From 6874d2b57fc1fa46a7e996b9813ff9edffaecf88 Mon Sep 17 00:00:00 2001 From: Patrick von Platen Date: Thu, 1 Dec 2022 13:16:15 +0000 Subject: [PATCH] up --- docs/source/api/schedulers.mdx | 28 +++++++++++++++++++++++++++- 1 file changed, 27 insertions(+), 1 deletion(-) diff --git a/docs/source/api/schedulers.mdx b/docs/source/api/schedulers.mdx index 7ed527bedf..82c4641cd7 100644 --- a/docs/source/api/schedulers.mdx +++ b/docs/source/api/schedulers.mdx @@ -76,6 +76,33 @@ Original paper can be found [here](https://arxiv.org/abs/2206.00927) and the [im [[autodoc]] DPMSolverMultistepScheduler +#### Heun scheduler inspired by Karras et. al paper + +Algorithm 1 of [Karras et. al](https://arxiv.org/abs/2206.00364). +Scheduler ported from @crowsonkb's https://github.com/crowsonkb/k-diffusion library: + +All credit for making this scheduler work goes to [Katherine Crowson](https://github.com/crowsonkb/) + +[[autodoc]] HeunDiscreteScheduler + +#### DPM Discrete Scheduler inspired by Karras et. al paper + +Inspired by [Karras et. al](https://arxiv.org/abs/2206.00364). +Scheduler ported from @crowsonkb's https://github.com/crowsonkb/k-diffusion library: + +All credit for making this scheduler work goes to [Katherine Crowson](https://github.com/crowsonkb/) + +[[autodoc]] KDPM2DiscreteScheduler + +#### DPM Discrete Scheduler with ancestral sampling inspired by Karras et. al paper + +Inspired by [Karras et. al](https://arxiv.org/abs/2206.00364). +Scheduler ported from @crowsonkb's https://github.com/crowsonkb/k-diffusion library: + +All credit for making this scheduler work goes to [Katherine Crowson](https://github.com/crowsonkb/) + +[[autodoc]] KDPM2AncestralDiscreteScheduler + #### Variance exploding, stochastic sampling from Karras et. al Original paper can be found [here](https://arxiv.org/abs/2006.11239). @@ -86,7 +113,6 @@ Original paper can be found [here](https://arxiv.org/abs/2006.11239). Original implementation can be found [here](https://arxiv.org/abs/2206.00364). - [[autodoc]] LMSDiscreteScheduler #### Pseudo numerical methods for diffusion models (PNDM)