* build base images for torch 2.7.1
* fix: update base docker to use torch 2.7.1
* fix: update doc for main base to use 2.7.1
* make sure to install fa2 in base uv too
* use no build isolation for uv+flashattn
* install psutil also for fa2
* longer timeout for flash attn build
---------
Co-authored-by: NanoCode012 <nano@axolotl.ai>
* feat: add llama4 multimodal
* feat: add torchvision to base docker
* just use latest torchvision
---------
Co-authored-by: Wing Lian <wing@axolotl.ai>
* add 12.8.1 cuda to the base matrix
* use nightly
* bump deepspeed and set no binary
* deepspeed binary fixes hopefully
* install deepspeed by itself
* multiline fix
* make sure ninja is installed
* try with reversion of packaging/setuptools/wheel install
* use license instead of license-file
* try rolling back packaging and setuptools versions
* comment out license for validation for now
* make sure packaging version is consistent
* more parity across tests and docker images for packaging/setuptools
* current
not clean working version
move torch trainer to do_cli
update code with config changes and clean up
edit config
cleanup
add run name to trainer
* address comments
* use axolotl train in multigpu tests and add ray tests for multi-gpu
* accelerate uses underscores for main_process_port arg
* chore: lint
* fix order of accelerate args
* include ray train in docker images
* current
not clean working version
move torch trainer to do_cli
update code with config changes and clean up
edit config
cleanup
add run name to trainer
* address comments
* use axolotl train in multigpu tests and add ray tests for multi-gpu
* accelerate uses underscores for main_process_port arg
* chore: lint
* fix order of accelerate args
* include ray train in docker images
* fix bf16 resolution behavior
* move dtype logic
* x
Signed-off-by: SumanthRH <sumanthrh@anyscale.com>
* rename
Signed-off-by: SumanthRH <sumanthrh@anyscale.com>
* add to sidebar
Signed-off-by: SumanthRH <sumanthrh@anyscale.com>
* Apply suggestions from code review
Co-authored-by: Eric Tang <46737979+erictang000@users.noreply.github.com>
* Update docs/ray-integration.qmd
Co-authored-by: Eric Tang <46737979+erictang000@users.noreply.github.com>
* pre-commit fixes
Signed-off-by: SumanthRH <sumanthrh@anyscale.com>
* use output_dir instead of hardcoded saves path
Co-authored-by: NanoCode012 <kevinvong@rocketmail.com>
* bugfix storage dir
* change type\ for resources_per_worker
---------
Signed-off-by: SumanthRH <sumanthrh@anyscale.com>
Co-authored-by: Wing Lian <wing@axolotl.ai>
Co-authored-by: SumanthRH <sumanthrh@anyscale.com>
Co-authored-by: Sumanth R Hegde <39546518+SumanthRH@users.noreply.github.com>
Co-authored-by: Wing Lian <wing.lian@gmail.com>
Co-authored-by: NanoCode012 <kevinvong@rocketmail.com>
* fix build w pyproject to respect insalled torch version
* include in manifest
* disable duplicate code check for now
* move parser so it can be found
* add checks for correct pytorch version so this doesn't slip by again
* allow flexibility in transformers version for FSDP
* more flexibility with dev versions of 4.47.0.dev0
* add patch for fsdp
* fix typo
* correct fn name
* stray character
* fix patch
* reset Trainer too
* also reset Trainer.training_step
* allow tests/patched to run more than one process on e2e runner
* skip tests/patched in e2e for now since it's run in regular pytest
* bump transformers and trl
* fix: update trainer.log signature
* fix trl trainer.log interfaces
* broken 🦥 with latest transformers
* skip parent, call grandparent - yeah, super janky
* update HF HUB env var and fix reward trainer log since it doesn't directly override log
* also bump accelerate
* patches for llama ga
* detab the code to check
* fix whitespace for patch check
* play nicely with CI tests since we patch everytime
* fix pop default in case it doesn't exist
* more tweaks to make patches nicer in CI
* fix detab for when there are possibly multiple patches
---------
Co-authored-by: NanoCode012 <nano@axolotl.ai>
* feat: add cut_cross_entropy
* fix: add to input
* fix: remove from setup.py
* feat: refactor into an integration
* chore: ignore lint
* feat: add test for cce
* fix: set max_steps for liger test
* chore: Update base model following suggestion
Co-authored-by: Wing Lian <wing.lian@gmail.com>
* chore: update special_tokens following suggestion
Co-authored-by: Wing Lian <wing.lian@gmail.com>
* chore: remove with_temp_dir following comments
* fix: plugins aren't loaded
* chore: update quotes in error message
* chore: lint
* chore: lint
* feat: enable FA on test
* chore: refactor get_pytorch_version
* fix: lock cce commit version
* fix: remove subclassing UT
* fix: downcast even if not using FA and config check
* feat: add test to check different attentions
* feat: add install to CI
* chore: refactor to use parametrize for attention
* fix: pytest not detecting test
* feat: handle torch lower than 2.4
* fix args/kwargs to match docs
* use release version cut-cross-entropy==24.11.4
* fix quotes
* fix: use named params for clarity for modal builder
* fix: handle install from pip
* fix: test check only top level module install
* fix: re-add import check
* uninstall existing version if no transformers submodule in cce
* more dataset fixtures into the cache
---------
Co-authored-by: Wing Lian <wing.lian@gmail.com>
Co-authored-by: Wing Lian <wing@axolotl.ai>
* see if unsloth installs cleanly in ci
* check unsloth install on regular tests, not sdist
* fix ampere check exception for ci
* use cached_property instead
* add an e2e test for unsloth qlora
* reduce seq len and mbsz to prevent oom in ci
* add checks for fp16 and sdp_attention
* pin unsloth to a specific release
* add unsloth to docker image too
* fix flash attn xentropy patch
* fix loss, add check for loss when using fa_xentropy
* fix special tokens for test
* typo
* test fa xentropy with and without gradient accum
* pr feedback changes
* fix 405b with lower cpu ram requirements
* make sure to use doouble quant and only skip output embeddings
* set model attributes
* more fixes for sharded fsdp loading
* update the base model in example to use pre-quantized nf4-bf16 weights
* upstream fixes for qlora+fsdp
* 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
* 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
* wip modal for ci
* handle falcon layernorms better
* update
* rebuild the template each time with the pseudo-ARGS
* fix ref
* update tests to use modal
* cleanup ci script
* make sure to install jinja2 also
* kickoff the gh action on gh hosted runners and specify num gpus
* add a basic notebook for lab users in the root
* update notebook and fix cors for jupyter
* cell is code
* fix eval batch size check
* remove intro notebook
* attempt to also run e2e tests that needs gpus
* fix stray quote
* checkout specific github ref
* dockerfile for tests with proper checkout
ensure wandb is dissabled for docker pytests
clear wandb env after testing
clear wandb env after testing
make sure to provide a default val for pop
tryin skipping wandb validation tests
explicitly disable wandb in the e2e tests
explicitly report_to None to see if that fixes the docker e2e tests
split gpu from non-gpu unit tests
skip bf16 check in test for now
build docker w/o cache since it uses branch name ref
revert some changes now that caching is fixed
skip bf16 check if on gpu w support
* pytest skip for auto-gptq requirements
* skip mamba tests for now, split multipack and non packed lora llama tests
* split tests that use monkeypatches
* fix relative import for prev commit
* move other tests using monkeypatches to the correct run
* 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
