* 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
