GitLab

pass tracker name as argumentw

* add: experimental script for diffusion dpo training.

* random_crop cli.

* fix: caption tokenization.

* fix: pixel_values index.

* fix: grad?

* debug

* fix: reduction.

* fixes in the loss calculation.

* style

* fix: unwrap call.

* fix: validation inference.

* add: initial sdxl script

* debug

* make sure images in the tuple are of same res

* fix model_max_length

* report print

* boom

* fix: numerical issues.

* fix: resolution

* comment about resize.

* change the order of the training transformation.

* save call.

* debug

* remove print

* manually detaching necessary?

* use the same vae for validation.

* add: readme.

* post release

* style

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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Fix gradient-checkpointing option is ignored in SDXL+LoRA training. (#6388)

* Fix gradient-checkpointing option is ignored in SD+LoRA training.

* Fix gradient checkpoint is not applied to text encoders. (SDXL+LoRA)

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* add to dreambooth lora.

* add: t2i lora.

* add: sdxl t2i lora.

* style

* lcm lora sdxl.

* unwrap

* fix: enable_adapters().

fix RuntimeError: Input type (float) and bias type (c10::Half) should be the same in train_text_to_image_lora.py (#6259)

* fix RuntimeError: Input type (float) and bias type (c10::Half) should be the same

* format source code

* format code

* remove the autocast blocks within the pipeline

* add autocast blocks to pipeline caller in train_text_to_image_lora.py

* initialize alpha too.

* add: test

* remove config parsing

* store rank

* debug

* remove faulty test

* fix: unscale fp16 gradient problem

* fix for dreambooth lora sdxl

* make the type-casting conditional.

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update train_text_to_image_lora.py

* Fix typo?

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Co-authored-by: M. Tolga Cangöz <46008593+standardAI@users.noreply.github.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

remove depcreated method from lora scripts.

* adapt example scripts to use PEFT

* Update examples/text_to_image/train_text_to_image_lora.py

* fix

* add for SDXL

* oops

* make sure to install peft

* fix

* fix

* fix dreambooth and lora

* more fixes

* add peft to requirements.txt

* fix

* final fix

* add peft version in requirements

* remove comment

* change variable names

* add few lines in readme

* add to reqs

* style

* fix issues

* fix lora dreambooth xl tests

* init_lora_weights to gaussian and add out proj where missing

* ammend requirements.

* ammend requirements.txt

* add correct peft versions

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Post Release: v0.24.0

* post pone deprecation

* post pone deprecation

* Add model_index.json

* add variant

* add variant

* Apply suggestions from code review

* reformat

* fix: textual_inversion.py

* fix: variant in model_info

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Co-authored-by: sayakpaul <spsayakpaul@gmail.com>

* [Lora] Seperate logic

* [Lora] Seperate logic

* [Lora] Seperate logic

* add comments to explain the code better

* add comments to explain the code better

* post release

* fix: variant test

* up

* fix: test

post release

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>

* fix: how print training resume logs.

* propagate changes to text-to-image scripts.

* propagate changes to instructpix2pix.

* propagate changes to dreambooth

* propagate changes to custom diffusion and instructpix2pix

* propagate changes to kandinsky

* propagate changes to textual inv.

* debug

* fix: checkpointing.

* debug

* debug

* debug

* back to the square

* debug

* debug

* change condition order.

* debug

* debug

* debug

* debug

* revert to original

* clean

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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

add compute_snr() to training utils.

* merge with main

* fix flax example

* fix onnx example

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Co-authored-by: bghira <bghira@users.github.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Co-authored-by: bghira <bghira@users.github.com>

* [Release 0.21] Bump version

* fix & remove

* fix more

* fix all, upload

Co-authored-by: AisingioroHao0 <1286098622@qq.com>

* 0.20.0dev0

* make style

* Multiply lr scheduler steps by `num_processes`.

* Stop multiplying steps by gradient accumulation.

* add rank args in lora finetune

* del network_alpha

* manual check for checkpoints_total_limit instead of using accelerate

* remove controlnet_conditioning_embedding_out_channels

* relax tolerance slightly

* correct incorrect naming

* Post release

* Post release

Apply deprecations

* Implement option for rescaling betas to zero terminal SNR

* Implement rescale classifier free guidance in pipeline_stable_diffusion.py

* focus on DDIM

* make style

* make style

* make style

* make style

* Apply suggestions from Peter Lin

* Apply suggestions from Peter Lin

* make style

* Apply suggestions from code review

* Apply suggestions from code review

* make style

* make style

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Co-authored-by: MaxWe00 <gitlab.9v1lq@slmail.me>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

add min snr to text2img lora training script

* Post release

* fix more

* [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