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increase the time of timeout when using big dataset or high resolution

* avoid upcasting by assigning dtype to noise tensor

* make style

* Update train_unconditional.py

* Update train_unconditional.py

* make style

* add unit test for pickle

* revert change

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Co-authored-by: root <root@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Prathik Rao <prathikrao@microsoft.com@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>

* manual check for checkpoints_total_limit instead of using accelerate

* remove controlnet_conditioning_embedding_out_channels

* Post release

* Post release

Apply deprecations

* Post release

* fix more

* Fix tensorboard tracking with `accelerate` @ `main`

* Fix `train_unconditional.py` with accelerate from main.

This reverts commit 024c4376.

* 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.

* [Examples] Test all examples on CPU

* add

* correct

* Apply suggestions from code review

* EMA: fix `state_dict()` & add `cur_decay_value`

* EMA: fix a bug in `load_state_dict()`

'float' object (`state_dict["power"]`) has no attribute 'get'.

* del train_unconditional_ort.py

* before running make style

* remove left overs from flake8

* finish

* make fix-copies

* final fix

* more fixes

* better accelerated saving

* up

* finish

* finish

* uP

* up

* up

* fix

* Apply suggestions from code review

* correct ema

* Remove @

* up

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/training/dreambooth.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

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Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* 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

* Don't copy when unwrapping model.

Otherwise an exception is raised when using fp16.

* Remove unused import

* [Bump version] 0.13

* Bump model up

* up

* Create repo before cloning in examples

* code quality

* improve EMA

* style

* one EMA model

* quality

* fix tests

* fix test

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* re organise the unconditional script

* backwards compatibility

* default to init values for some args

* fix ort script

* issubclass => isinstance

* update state_dict

* docstr

* doc

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* use .to if device is passed

* deprecate device

* make flake happy

* fix typo
Co-authored-by: patil-suraj <surajp815@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

fix lr scheduler

Update train_unconditional.py

Add logger flag to choose between tensorboard and wandb

* 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>