use a constraint file
use min version of xformers
don't install autoawq with pytorch 2.5.0
debugging for errors
upgrade pip first
fix action yml
add back try/except
retry w/o constraint
use --no-build-isolation
show torch version
install setuptools and wheel
add back try/except
* add support for optimi_adamw optimizer w kahan summation
* pydantic validator for optimi_adamw
* workaround for setting optimizer for fsdp
* make sure to install optimizer packages
* make sure to have parity for model parameters passed to optimizer
* add smoke test for optimi_adamw optimizer
* don't use foreach optimi by default
* bump flash attention 2.5.8 -> 2.6.1
* use triton implementation of cross entropy from flash attn
* add smoke test for flash attn cross entropy patch
* fix args to xentropy.apply
* handle tuple from triton loss fn
* ensure the patch tests run independently
* use the wrapper already built into flash attn for cross entropy
* mark pytest as forked for patches
* use pytest xdist instead of forked, since cuda doesn't like forking
* limit to 1 process and use dist loadfile for pytest
* change up pytest for fixture to reload transformers w monkeypathc
* Update requirements.txt
Preserve compatibility with torch 2.3.1. [Reference](https://github.com/facebookresearch/xformers/issues/1052)
* fix setup.py to extract the current xformers dep from requirements for replacement
* xformers 0.0.27 wheels not built for torch 2.3.0
---------
Co-authored-by: Wing Lian <wing.lian@gmail.com>
* support galore once upstreamed into transformers
* update module name for llama in readme and fix typing for all linear
* bump trl for deprecation fixes from newer transformers
* include galore as an extra and install in docker image
* fix optim_args type
* fix optim_args
* update dependencies for galore
* add galore to cicd dockerfile
* make mlflow optional
* fix xformers
don't patch swiglu if xformers not working
fix the check for xformers swiglu
* fix install of xformers with extra index url for docker builds
* fix docker build arg quoting
* add mps support
* linter stuff
* CI fixes
* install packaging for various tests
* Update setup.py
* Revert "install packaging for various tests"
This reverts commit 980e7aa44d.
* Revert "CI fixes"
This reverts commit 4609e3b166.
---------
Co-authored-by: Wing Lian <wing.lian@gmail.com>
* restore to current phi modeling code from phi-2
* enable gradient checkpointing
* don't cast everything to float32 all the time
* gradient checkpointing for phi2 ParallelBlock module too
* fix enabling flash attn for phi2
* add comment about import
* fix phi2 example
* fix model type check for tokenizer
* revert float32 -> bf16 casting changes
* support fused dense flash attn
* fix the repo for flash-attn
* add package name for subdir pkg
* fix the data collator when not using sample packing
* install packaging for pytests in ci
* also fix setup to not install flash attn fused dense subdir if not extras
* split out the fused-dense-lib in extra requires
* don't train w group_by_length for phi
* update integration test to use phi2
* set max steps and save steps for phi e2e tests
* try to workaround ssave issue in ci
* skip phi2 e2e test for now
* add torch to requirements.txt at build time to force version to stick
* fix xformers check
* better handling of xformers based on installed torch version
* fix for ci w/o torch
* support for mamba
* more mamba fixes
* use fork for mamba kwargs fix
* grad checkpointing doesn't work
* fix extras for mamaba
* mamba loss fix
* use fp32 and remove verbose logging
* mamba fixes
* fix collator for mamba
* set model_type on training_args
* don't save safetensors for mamba
* update mamba config to disable safetensor checkpooints, install for tests
* no evals for mamba tests
* handle save_pretrained
* handle unused safetensors arg
* update readme to point to direct link to runpod template, cleanup install instrucitons
* default install flash-attn and auto-gptq now too
* update readme w flash-attn extra
* fix version in setup
* auto gptq support
* more tweaks and add yml
* remove old gptq docker
* don't need explicit peft install for tests
* fix setup.py to use extra index url
install torch for tests
fix cuda version for autogptq index
set torch in requirements so that it installs properly
move gptq install around to work with github cicd
* gptq doesn't play well with sample packing
* address pr feedback
* remove torch install for now
* set quantization_config from model config
* Fix the implementation for getting quant config from model config
* recast loralayer, norm, lmhead + embed token weights per original qlora
* try again for the fix
* refactor torch dtype picking
* linter fixes
* missing import for LoraLayer
* fix install for tests now that peft is involved
* flash attn pip
* add packaging
* add packaging to apt get
* install flash attn in dockerfile
* remove unused whls
* add wheel
* clean up pr
fix packaging requirement for ci
upgrade pip for ci
skip build isolation for requiremnents to get flash-attn working
install flash-attn seperately
* install wheel for ci
* no flash-attn for basic cicd
* install flash-attn as pip extras
---------
Co-authored-by: Ubuntu <mgh@mgh-vm.wsyvwcia0jxedeyrchqg425tpb.ax.internal.cloudapp.net>
Co-authored-by: mhenrichsen <some_email@hey.com>
Co-authored-by: Mads Henrichsen <mads@BrbartiendeMads.lan>
Co-authored-by: Wing Lian <wing.lian@gmail.com>
