GitLab

* finish

* finish

* Update src/diffusers/modeling_utils.py

* Update src/diffusers/pipeline_utils.py
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

* more fixes

* fix
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

* 2x speedup using memory efficient attention

* remove einops dependency

* Swap K, M in op instantiation

* Simplify code, remove unnecessary maybe_init call and function, remove unused self.scale parameter

* make xformers a soft dependency

* remove one-liner functions

* change one letter variable to appropriate names

* Remove Env variable dependency, remove MemoryEfficientCrossAttention class and use enable_xformers_memory_efficient_attention method

* Add memory efficient attention toggle to img2img and inpaint pipelines

* Clearer management of xformers' availability

* update optimizations markdown to add info about memory efficient attention

* add benchmarks for TITAN RTX

* More detailed explanation of how the mem eff benchmark were ran

* Removing autocast from optimization markdown

* import_utils: import torch only if is available
Co-authored-by: Nouamane Tazi <nouamane98@gmail.com>

* Fix pipelines user_agent, ignore CI requests

* fix circular import

* N/A versions

* N/A versions

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

* Fix is_onnx_available

Fix: If user install onnxruntime-gpu, is_onnx_available() will return False.

* add more onnxruntime candidates

* Run `make style`
Co-authored-by: anton-l <anton@huggingface.co>

* initial export and design

* update imports

* custom prover, import fixes

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

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

* remove push_to_hub

* Update src/diffusers/onnx_utils.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* remove torch_device

* numpify the rest of the pipeline

* torchify the safety checker

* revert tensor

* Code review suggestions + quality

* fix tests

* fix provider, add an end-to-end test

* style
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Add is_<framework>_available, refactor import utils

* deps

* quality