GitLab

* update flax scheduler API

* remoev set format

* fix call to scale_model_input

* update flax pndm

* use int32

* update docstr

* Add diffusers version and pipeline class to the Hub UA

* Fallback to class name for pipelines

* Update src/diffusers/modeling_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/modeling_flax_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

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

* fix ema

* style

* add comment about copy

* style

* quality

* add or fix license formatting

* fix quality

This reverts commit 679c77f8.

* [Dummy imports] Better error message

* Test: load pipeline with LMS scheduler.

Fails with a cryptic message if scipy is not installed.

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

* [Img2Img] Fix batch size mismatch prompts vs. init images

* Remove bogus folder

* fix

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* mps: alt. implementation for repeat_interleave

* style

* Bump mps version of PyTorch in the documentation.

* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Simplify: do not check for device.

* style

* Fix repeat dimensions:

- The unconditional embeddings are always created from a single prompt.
- I was shadowing the batch_size var.

* Split long lines as suggested by Suraj.
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

Update custom_pipelines.mdx

* pass norm_num_groups param and add tests

* set resnet_groups for FlaxUNetMidBlock2D

* fixed docstrings

* fixed typo

* using is_flax_available util and created require_flax decorator

* begin text2image script

* loading the datasets, preprocessing & transforms

* handle input features correctly

* add gradient checkpointing support

* fix output names

* run unet in train mode not text encoder

* use no_grad instead of freezing params

* default max steps None

* pad to longest

* don't pad when tokenizing

* fix encode on multi gpu

* fix stupid bug

* add random flip

* add ema

* fix ema

* put ema on cpu

* improve EMA model

* contiguous_format

* don't warp vae and text encode in accelerate

* remove no_grad

* use randn_like

* fix resize

* improve few things

* log epoch loss

* set log level

* don't log each step

* remove max_length from collate

* style

* add report_to option

* make scale_lr false by default

* add grad clipping

* add an option to use 8bit adam

* fix logging in multi-gpu, log every step

* more comments

* remove eval for now

* adress review comments

* add requirements file

* begin readme

* begin readme

* fix typo

* fix push to hub

* populate readme

* update readme

* remove use_auth_token from the script

* address some review comments

* better mixed precision support

* remove redundant to

* create ema model early

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

* better description for train_data_dir

* add diffusers in requirements

* update dataset_name_mapping

* update readme

* add inference example
Co-authored-by: anton-l <anton@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* support bf16 for stable diffusion

* fix typo

* address review comments

* Support deepspeed

* Dreambooth DeepSpeed documentation

* Remove unnecessary casts, documentation

Due to recent commits some casts to half precision are not necessary
anymore.

Mention that DeepSpeed's version of Adam is about 2x faster.

* Review comments

fix typo docstring

* Fix gradient checkpointing test

* more tsets

* add accelerate to load models with smaller memory footprint

* remove low_cpu_mem_usage as it is reduntant

* move accelerate init weights context to modelling utils

* add test to ensure results are the same when loading with accelerate

* add tests to ensure ram usage gets lower when using accelerate

* move accelerate logic to single snippet under modelling utils and remove it from configuration utils

* format code using to pass quality check

* fix imports with isor

* add accelerate to test extra deps

* only import accelerate if device_map is set to auto

* move accelerate availability check to diffusers import utils

* format code

* add device map to pipeline abstraction

* lint it to pass PR quality check

* fix class check to use accelerate when using diffusers ModelMixin subclasses

* use low_cpu_mem_usage in transformers if device_map is not available

* NoModuleLayer

* comment out tests

* up

* uP

* finish

* Update src/diffusers/pipelines/stable_diffusion/safety_checker.py

* finish

* uP

* make style
Co-authored-by: Pi Esposito <piero.skywalker@gmail.com>

* add sigmoid betas

* convert to torch

* add comment on source

* clean up resnet.py

* make style and quality

* minor formatting

* debug an exception

if dst_path is not a file, it will raise Exception in the function src_path.samefile:
FileNotFoundError: [Errno 2] No such file or directory: '/home/lilongwei/notebook/onnx_diffusion/vae_decoder/model.onnx'

* Update src/diffusers/onnx_utils.py
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Fix tests

* remove bogus file

* handle dtype in vae and image2image pipeline

* fix inpaint in fp16

* dtype should be handled in add_noise

* style

* address review comments

* add simple fast tests to check fp16

* fix test name

* put mask in fp16

* handle dtype in vae and image2image pipeline

* handle dtype in add noise

* don't modify vae and pipeline

* remove the if

Otherwise, it crashes when eta > 0 with float16.

This is to ensure that the final latent slices stay somewhat consistent as more changes are introduced into the library.
Signed-off-by: James R T <jamestiotio@gmail.com>
Signed-off-by: James R T <jamestiotio@gmail.com>

The opset argument should be an `int` but was set as a `str`.

* Fix push_to_hub for dreambooth and textual_inversion

* Use repo.push_to_hub instead of push_to_hub

* Swap fp16 error to warning

Also remove the associated test

* Formatting

* warn -> warning

* Update src/diffusers/pipeline_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

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

This reverts commit 95311501.

[Tests] Lower required memory for clip guided and fix super edge-case git pipeline module bug (#754)

* [Tests] Lower required memory

* fix

* up

* uP