* fixed vae loading issue #7619
* rerun make style && make quality
* bring back model_has_vae and add change \ to / in config_file_name on windows os to make match work
* add missing import platform
* bring back import model_info
* make config_file_name OS independent
* switch to using Path.as_posix() to resolve OS dependence
* improve style
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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: bssrdf <bssrdf@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.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 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
* feat: standarize model card creation for dreambooth training.
* correct 'inference
* remove comments.
* take component out of kwargs
* style
* add: card template to have a leaner description.
* widget support.
* propagate changes to train_dreambooth_lora
* propagate changes to custom diffusion
* make widget properly type-annotated
* support compile
* make style
* move unwrap_model inside function
* change unwrap call
* run make style
* Update examples/dreambooth/train_dreambooth.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Revert "Update examples/dreambooth/train_dreambooth.py"
This reverts commit 70ab09732e.
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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* min-SNR gamma for Dreambooth training
* Align the mse_loss_weights style with SDXL training example
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Co-authored-by: bghira <bghira@users.github.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* dreambooth training
* train_dreambooth validation scheduler
* set a particular scheduler via a string
* modify readme after setting a particular scheduler via a string
* modify readme after setting a particular scheduler
* use importlib to set a particular scheduler
* import with correct sort
Ethan Smith