* [docs] Replace runwayml/stable-diffusion-v1-5 with Lykon/dreamshaper-8
Updated documentation as runwayml/stable-diffusion-v1-5 has been removed from Huggingface.
* Update docs/source/en/using-diffusers/inpaint.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Replace with stable-diffusion-v1-5/stable-diffusion-v1-5
* Update inpaint.md
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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* 7879 - adjust documentation to use naruto dataset, since pokemon is now gated
* replace references to pokemon in docs
* more references to pokemon replaced
* Japanese translation update
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Co-authored-by: bghira <bghira@users.github.com>
* 7529 do not disable autocast for cuda devices
* Remove typecasting error check for non-mps platforms, as a correct autocast implementation makes it a non-issue
* add autocast fix to other training examples
* disable native_amp for dreambooth (sdxl)
* disable native_amp for pix2pix (sdxl)
* remove tests from remaining files
* disable native_amp on huggingface accelerator for every training example that uses it
* convert more usages of autocast to nullcontext, make style fixes
* make style fixes
* style.
* Empty-Commit
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Co-authored-by: bghira <bghira@users.github.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Add properties and `IPAdapterTesterMixin` tests for `StableDiffusionPanoramaPipeline`
* Fix variable name typo and update comments
* Update deprecated `output_type="numpy"` to "np" in test files
* Discard changes to src/diffusers/pipelines/stable_diffusion_panorama/pipeline_stable_diffusion_panorama.py
* Update test_stable_diffusion_panorama.py
* Update numbers in README.md
* Update get_guidance_scale_embedding method to use timesteps instead of w
* Update number of checkpoints in README.md
* Add type hints and fix var name
* Fix PyTorch's convention for inplace functions
* Fix a typo
* Revert "Fix PyTorch's convention for inplace functions"
This reverts commit 74350cf65b.
* Fix typos
* Indent
* Refactor get_guidance_scale_embedding method in LEditsPPPipelineStableDiffusionXL class
* add tags for diffusers training
* add tags for diffusers training
* add tags for diffusers training
* add tags for diffusers training
* add tags for diffusers training
* add tags for diffusers training
* add dora tags for drambooth lora scripts
* style
* fix minsnr implementation for v-prediction case
* format code
* always compute snr when snr_gamma is specified
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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
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 <bghira@users.github.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* update code to reflect latest changes as of May 30th
* update text to image example
* reflect changes to textual inversion
* make style
* fix typo
* Revert unnecessary readme changes
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Co-authored-by: root <root@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
Co-authored-by: Prathik Rao <prathikrao@microsoft.com@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
* [Config] Fix config prints and save, load
* Only use potential nn.Modules for dtype and device
* Correct vae image processor
* make sure in_channels is not accessed directly
* make sure in channels is only accessed via config
* Make sure schedulers only access config attributes
* Make sure to access config in SAG
* Fix vae processor and make style
* add tests
* uP
* make style
* Fix more naming issues
* Final fix with vae config
* change more
* 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
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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Will Berman <wlbberman@gmail.com>
* add total number checkpoints to training scripts
* Update examples/dreambooth/train_dreambooth.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Log Unconditional Image Generation Samples to WandB
* Check for wandb installation and parity between onnxruntime script
* Log epoch to wandb
* Check for tensorboard logger early on
* style fixes
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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Resolves ValueError: `num_inference_steps`: 1000 cannot be larger than `self.config.train_timesteps`: 50 as the unet model trained with this scheduler can only handle maximal 50 timesteps.
* Fix torchvision.transforms and transforms function naming clash
* Update unconditional script for onnx
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Add center crop and horizontal flip to args
* Update command to use center crop and random flip
* Add center crop and horizontal flip to args
* Update command to use center crop and random flip
