GitLab

* Post release

* Post release

* Post release

* fix more

extract pipeline from log_validation

* WIP controlnet training

- bugfix --streaming
- bugfix running report_to!='wandb'
- adds memory profile before validation

* Adds final logging statement.

* Sets train epochs to 11.

Looking at a longer ~16ep run, we see only good validation images
after ~11ep:

https://wandb.ai/andsteing/controlnet_fill50k/runs/3j2hx6n8



* Removes --logging_dir (it's not used).

* Adds --profile flags.

* Updates --output_dir=runs/fill-circle-{timestamp}.

* Compute mean of `train_metrics`.

Previously `train_metrics[-1]` was logged, resulting in very bumpy train
metrics.

* Improves logging a bit.

- adds l2_grads gradient norm logging
- adds steps_per_sec
- sets walltime as x coordinate of train/step
- logs controlnet_params config

* Adds --ccache (doesn't really help though).

* minor fix in controlnet flax example (#2986)

* fix the error when push_to_hub but not log validation

* contronet_from_pt & controlnet_revision

* add intermediate checkpointing to the guide

* Bugfix --profile_steps

* Sets `RACKER_PROJECT_NAME='controlnet_fill50k'`.

* Logs fractional epoch.

* Adds relative `walltime` metric.

* Adds `StepTraceAnnotation` and uses `global_step` insetad of `step`.

* Applied `black`.

* Streamlines commands in README a bit.

* Removes `--ccache`.

This makes only a very small difference (~1 min) with this model size, so removing
the option introduced in cdb3cc.

* Re-ran `black`.

* Update examples/controlnet/README.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Converts spaces to tab.

* Removes repeated args.

* Skips first step (compilation) in profiling

* Updates README with profiling instructions.

* Unifies tabs/spaces in README.

* Re-ran style & quality.

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

* add wandb team and min-snr loss

* make style

* apply feedbacks

* fix the error when push_to_hub but not log validation

* contronet_from_pt & controlnet_revision

* add intermediate checkpointing to the guide

* load_from_disk + checkpointing_steps

* apply feedback

use custom local datset
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

use upload folder in training scripts
Co-authored-by: testbot <lucainp@hf.co>

* ensure validation image RGB not RGBA

* ensure validation image RGB not RGBA

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

* improve stable unclip doc.

* feat: add streaming support to controlnet flax training script.

* fix: CLI arg.

* fix: torch dataloader shuffle setting.

* fix: dataset length.

* fix: wandb config.

* fix: steps_per_epoch in the training loop.

* add: entry about streaming in the readme

* get column names from iterable dataset + fix final logging

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Co-authored-by: yiyixuxu <yixu310@gmail.com>

* add train_controlnet_flax

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