* 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
* Create convert_vae_pt_to_diffusers.py
Just a simple script to convert VAE.pt files to diffusers format
Tested with: https://huggingface.co/WarriorMama777/OrangeMixs/blob/main/VAEs/orangemix.vae.pt
* Update convert_vae_pt_to_diffusers.py
Forgot to add the function call
* make style
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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: chavinlo <example@example.com>
* make scaling factor cnfig arg of vae
* fix
* make flake happy
* fix ldm
* fix upscaler
* qualirty
* Apply suggestions from code review
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* solve conflicts, addres some comments
* examples
* examples min version
* doc
* fix type
* typo
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_upscale.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* remove duplicate line
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* implemented multi subject dreambooth in research_projects
* minor edits to readme
* added style and quality fixes
Co-authored-by: Krista Opsahl-Ong <kristaopsahlong@gmail.com>
* [Deterministic torch randn] Allow tensors to be generated on CPU
* fix more
* up
* fix more
* up
* Update src/diffusers/utils/torch_utils.py
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
* Apply suggestions from code review
* up
* up
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Section header for in-painting, inference from checkpoint.
* Inference: link to section to perform inference from checkpoint.
* Move Dreambooth in-painting instructions to the proper place.
* Add examples with Intel optimizations (BF16 fine-tuning and inference)
* Remove unused package
* Add README for intel_opts and refine the description for research projects
* Add notes of intel opts for diffusers
* Add state checkpointing to other training scripts
* Fix first_epoch
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update Dreambooth checkpoint help message.
* Dreambooth docs: checkpoints, inference from a checkpoint.
* make style
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add check_min_version for examples
* move __version__ to the top
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* fix comment
* fix error_message
* adapt the install message
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Isamu Isozaki