33 lines
2.7 KiB
Plaintext
33 lines
2.7 KiB
Plaintext
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<!--Copyright 2022 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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specific language governing permissions and limitations under the License.
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-->
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# Schedulers
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The base class ['SchedulerMixin'] implements low level utilities used by multiple schedulers.
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At a high level:
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- Schedulers are the algorithms to use diffusion models in inference as well as for training. They include the noise schedules and define algorithm-specific diffusion steps.
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- Schedulers can be used interchangable between diffusion models in inference to find the preferred tradef-off between speed and generation quality.
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- Schedulers are available in numpy, but can easily be transformed into PyTorch.
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## API
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- Schedulers should provide one or more `def step(...)` functions that should be called iteratively to unroll the diffusion loop during
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the forward pass.
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- Schedulers should be framework-agonstic, but provide a simple functionality to convert the scheduler into a specific framework, such as PyTorch
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with a `set_format(...)` method.
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## Examples
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- The ['DDPMScheduler'] was proposed in [Denoising Diffusion Probabilistic Models](https://arxiv.org/abs/2006.11239) and can be found in [scheduling_ddpm.py](https://github.com/huggingface/diffusers/blob/main/src/diffusers/schedulers/scheduling_ddpm.py).
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An example of how to use this scheduler can be found in [pipeline_ddpm.py](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/pipeline_ddpm.py).
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- The ['DDIMScheduler'] was proposed in [Denoising Diffusion Implicit Models](https://arxiv.org/abs/2010.02502) and can be found in [scheduling_ddim.py](https://github.com/huggingface/diffusers/blob/main/src/diffusers/schedulers/scheduling_ddim.py). An example of how to use this scheduler can be found in [pipeline_ddim.py](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/pipeline_ddim.py).
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- The ['PNMDScheduler'] was proposed in [Pseudo Numerical Methods for Diffusion Models on Manifolds](https://arxiv.org/abs/2202.09778) and can be found in [scheduling_pndm.py](https://github.com/huggingface/diffusers/blob/main/src/diffusers/schedulers/scheduling_pndm.py). An example of how to use this scheduler can be found in [pipeline_pndm.py](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/pipeline_pndm.py).
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