diffusers

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Files

Andy 116f70cbf8 Enabling gradient checkpointing for VAE (#2536 )

* updated black format

* update black format

* make style format

* updated line endings

* update code formatting

* Update examples/research_projects/onnxruntime/text_to_image/train_text_to_image.py

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/vae.py

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/vae.py

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* added vae gradient checkpointing test

* make style

---------

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Will Berman <wlbberman@gmail.com>

2023-03-17 14:59:38 -07:00

text_to_image

Enabling gradient checkpointing for VAE (#2536 )

2023-03-17 14:59:38 -07:00

textual_inversion

image generation main process checks (#2631 )

2023-03-14 01:28:03 -07:00

unconditional_image_generation

checkpointing_steps_total_limit->checkpoints_total_limit (#2374 )

2023-02-16 00:28:58 -08:00

README.md

refactor onnxruntime integration (#2042 )

2023-02-03 12:04:59 +01:00

README.md

Diffusers examples with ONNXRuntime optimizations

This research project is not actively maintained by the diffusers team. For any questions or comments, please contact Prathik Rao (prathikr), Sunghoon Choi (hanbitmyths), Ashwini Khade (askhade), or Peng Wang (pengwa) on github with any questions.

This aims to provide diffusers examples with ONNXRuntime optimizations for training/fine-tuning unconditional image generation, text to image, and textual inversion. Please see individual directories for more details on how to run each task using ONNXRuntime.