Merge changes #117
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Merge changes #117
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* add: entry for DDPO support. * move to training * address steven's comments./
#5238) Min-SNR Gamma: correct the fix for SNR weighted loss in v-prediction by adding 1 to SNR rather than the resulting loss weights Co-authored-by: bghira <[email protected]> Co-authored-by: Sayak Paul <[email protected]>
bump tolerance on shape test
…usionLatentUpscalePipeline (#5194) * add from single file * clean up * make style * add single file loading for upscaling
fix: torch.compile() for lora conv
* start * finish draft * add section * edits * feedback * make fix-copies * rebase
tiny fixes
* Update pipeline_wuerstchen_prior.py * prior_num_inference_steps updated * height, width, num_inference_steps, and guidance_scale synced * parameters synced * latent_mean, latent_std, and resolution_multiple synced * prior_num_inference_steps changed * Formatted pipeline_wuerstchen_prior.py * Update src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen_prior.py --------- Co-authored-by: Kashif Rasul <[email protected]>
Co-authored-by: YiYi Xu <[email protected]>
…ainting mode when EulerAncestralDiscreteScheduler is used (#5305) * fix(gligen_inpaint_pipeline): 🐛 Wrap the timestep() 0-d tensor in a list to convert to 1-d tensor. This avoids the TypeError caused by trying to directly iterate over a 0-dimensional tensor in the denoising stage * test(gligen/gligen_text_image): unit test using the EulerAncestralDiscreteScheduler --------- Co-authored-by: zhen-hao.chu <[email protected]> Co-authored-by: Sayak Paul <[email protected]>
* Update train_custom_diffusion.py * make style * Empty-Commit --------- Co-authored-by: Sayak Paul <[email protected]>
* Reduce number of down block channels * Remove debug code * Set new excepted image slice values for sdxl euler test
* decrease UNet2DConditionModel & ControlNetModel blocks * decrease UNet2DConditionModel & ControlNetModel blocks * decrease even more blocks & number of norm groups * decrease vae block out channels and n of norm goups * fix code style --------- Co-authored-by: Sayak Paul <[email protected]>
* improvement: add typehints and docs to diffusers/models/activations.py * improvement: add typehints and docs to diffusers/models/resnet.py
* add missing docstrings * chore: run make quality * improvement: include docs suggestion by @yiyixuxu --------- Co-authored-by: Patrick von Platen <[email protected]>
Update adapter.md to fix links to adapter pipelines
* Fix fuse Lora * improve a bit * make style * Update src/diffusers/models/lora.py Co-authored-by: Benjamin Bossan <[email protected]> * ciao C file * ciao C file * test & make style --------- Co-authored-by: Benjamin Bossan <[email protected]>
`jnp.array` is a function, not a type: https://jax.readthedocs.io/en/latest/_autosummary/jax.numpy.array.html so it never makes sense to use `jnp.array` in a type annotation. Presumably the intent was to write `jnp.ndarray` aka `jax.Array`. Change uses of `jnp.array` to `jnp.ndarray`. Co-authored-by: Peter Hawkins <[email protected]>
Update requirements_sdxl.txt Add missing 'datasets' Co-authored-by: Sayak Paul <[email protected]>
…5340) fix problem of 'accelerator.is_main_process' to run in mutiple GPUs or NPUs Co-authored-by: jiaqiw <[email protected]>
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