GitLab

* [WIP][CI] Framework and hardware-specific docker images for CI tests

* username

* fix cpu

* try out the image

* push latest

* update workspace

* no root isolation for actions

* add a flax image

* flax and onnx matrix

* fix runners

* add reports

* onnxruntime image

* retry tpu

* fix

* fix

* build onnxruntime

* naming

* onnxruntime-gpu image

* onnxruntime-gpu image, slow tests

* latest jax version

* trigger flax

* run flax tests in one thread

* fast flax tests on cpu

* fast flax tests on cpu

* trigger slow tests

* rebuild torch cuda

* force cuda provider

* fix onnxruntime tests

* trigger slow

* don't specify gpu for tpu

* optimize

* memory limit

* fix flax tests

* disable docker cache

* [Better scheduler docs] Improve usage examples of schedulers

* finish

* fix warnings and add test

* finish

* more replacements

* adapt fast tests hf token

* correct more

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

* Integrate compatibility with euler
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Fix pipelines user_agent, ignore CI requests

* fix circular import

* N/A versions

* N/A versions

* add method to enable cuda with minimal gpu usage to stable diffusion

* add test to minimal cuda memory usage

* ensure all models but unet are onn torch.float32

* move to cpu_offload along with minor internal changes to make it work

* make it test against accelerate master branch

* coming back, its official: I don't know how to make it test againt the master branch from accelerate

* make it install accelerate from master on tests

* go back to accelerate>=0.11

* undo prettier formatting on yml files

* undo prettier formatting on yml files againn

* [WIP] Debugging mps DDIM tests

* revert num_steps

* check warmup with a generator

* more warmup!

* remove xdist

* just use a single process

* [CI] Add Apple M1 tests

* setup-python

* python build

* conda install

* remove branch

* only 3.8 is built for osx-arm

* try fetching prebuilt tokenizers

* use user cache

* update shells

* Reports and cleanup

* -> MPS

* Disable parallel tests

* Better naming

* investigate worker crash

* return xdist

* restart

* num_workers=2

* still crashing?

* faulthandler for segfaults

* faulthandler for segfaults

* remove restarts, stop on segfault

* torch version

* change installation order

* Use pre-RC version of PyTorch.

To be updated when it is released.

* Skip crashing test on MPS, add new one that works.

* Skip cuda tests in mps device.

* Actually use generator in test.

I think this was a typo.

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

* [CI] Localize the HF cache

* pip cache

* de-env

* refactor matrix

* fix fast cache

* less onnx steps

* revert

* revert pip cache

* revert pip cache

* remove debugging trigger

* make_reports

* add test utils

* style

* style

Cancel pending jobs for PRs on new commits

* Init CI

* clarify cpu

* style

* Check scripts quality too

* Drop smi for cpu tests

* Run PR tests on cpu docker envs

* Update .github/workflows/push_tests.yml
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Try minimal python container

* Print env, install stable GPU torch

* Manual torch install

* remove deprecated platform.dist()
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>