* async grpo support
* implement data producer
* use fast async
* handle call to create data producer
* fix liger kernel setup
* fix replay buffer
* chore: lint
* make gpus go brrr
* chore: lint
* inplace div_, unwrap model for logits in bf16
* fuse selective softmax and empty cuda cache on each scoring step
* remove waiting for synch time and fix race
* make fp8 work and allow lora kernels w rl
* grpo with lora vllm sync and fixes for sharded distributed
* update docs
* more patches so it works against trl main
* address PR feedback for corerabbit
* fix: replace shell=True subprocess with argument list in modal CLI
Using shell=True with a formatted string containing docker_image
(a user-controlled value) is a command injection risk (Bandit B602).
Replace with an argument list, which passes args directly to the
process without shell interpretation, removing the nosec annotation.
* fix: add nosec annotation to suppress bandit B603/B607 warnings
Removing shell=True (B602) surfaces B603 (subprocess without shell)
and B607 (partial executable path for 'docker'). Use bare # nosec
to suppress both, consistent with other nosec usages in the codebase.
* consolidate behavioud of routing in scattermoe kernels
* collect telemetry on best chosen autotuned kernel
* properly collect data
* Fix property name and get smem too
* handle issues raised by coderabbit
* add tests for parity before refactoring
* fix: explicit set workflow permission and move secrets to necessary
steps only
* fix: comment
* fix: more permission restrict
* chore: add read for pypi
* docs: fix codestyle placeholders in CONTRIBUTING.md
Replace unresolved {codestyle} and {URLofCodestyle} template
variables with Ruff, the project's actual linter/formatter
as configured in .pre-commit-config.yaml.
* fix: replace bare except clauses with specific exception types
- quantization.py: use except ImportError for optional torchao imports
(consistent with line 48 which already uses ImportError correctly)
- cli/config.py: use except (RuntimeError, AssertionError) for CUDA
device property query
Prevents masking unrelated errors like KeyboardInterrupt or SystemExit.
* test: add unit tests for convert.py JSON/JSONL utilities
Cover FileReader, FileWriter, StdoutWriter, JsonParser,
JsonlSerializer, and JsonToJsonlConverter with 8 test cases
including roundtrip and edge case (empty list) scenarios.
Previously this module had zero test coverage.
* fix: address CodeRabbit review feedback
- quantization.py: catch (ImportError, RuntimeError) for optional
torchao imports; CUDA wheel/GPU mismatches raise RuntimeError,
not ImportError
- convert.py: remove unused output_file_path parameter from
JsonToJsonlConverter.convert() — FileWriter already holds the
output path from construction
- tests/test_convert.py: update call site to match new signature
The non-root user approach had multiple issues with RunPod
compatibility, sudo PATH handling, and tmux in exec sessions.
Restoring root as the default user for now.
* update setuptools so trl can be installed from main for nightlies
* run the nightly in the PR CI on change
* use range request, don't use cu129 in CI since it's not supported with AO
* run multigpu ci if CCE install script changes
* install flash-linear-attention
* handle prequant weights for fsdp2 and ensure loss is not zero
* fix type for cu_seqlen, uninstall causal_conv1d
* chore: lint
* uv pip uninstall doesn't need confirmation
* upgrade transformers==5.3.0 trl==0.29.0 kernels
* use latest deepspeed fixes
* use corect image for cleanup
* fix test outputs for tokenizer fixes upstream
* fix import:
* keep trl at 0.28.0
* handle updated API
* use latest trl since 0.28.0 doesn't work with latest transformers
* use trl experimental for pad to length
* monkeypatch trl with ORPOTrainer so liger doesn't croak
* upgrade accelerate
* more fixes
* move patch for orpotrainer
* load the imports later
* remove use_logits_to_keep
* fix loss_type arg as a list
* fetch hf cache from s3
* just manually download the missing model for now
* lint for pre-commit update
* a few more missing models on disk
* fix: loss_type internally now list
* fix: remove deprecated code and raise deprecate
* fix: remove unneeded blocklist
* fix: remove reliance on transformers api to find package available
* chore: refactor shim for less sideeffect
* fix: silent trl experimental warning
---------
Co-authored-by: NanoCode012 <nano@axolotl.ai>
* extend pytest-sdist timeout to 30 min for slow/flaky tests
* Also preload the cdn cache so it doesn't get stampeded
* fix yaml syntax
* missing fields
* can't pipe to dev/null
* Fix nightlies and add 2.10.0 to multi-gpu suite
* mxfp4 axo
* import lint
* test for qat mxfp4
* config for mxfp4
* add qat:
* pass base config
* MXFakeQuantizeConfig
* lint
* tune config so it fits in 32GB VRAM
---------
Co-authored-by: Wing Lian <wing@axolotl.ai>
* Fix fsdp2 sharding. Fix validation of ao version for lr groups
* remove validation since axolotl requires ao>0.13.0 already
* Move fully_shard of entire module for lora_embedding_A/B out of loop
* chore: lint
---------
Co-authored-by: bekk02 <ID+bekk02@users.noreply.github.com>
Co-authored-by: Wing Lian <wing@axolotl.ai>
* chore: rename without period
* feat: add glm45 air
* feat: add doc on expert quantization
* feat: update base readme with new changes
* chore: cleanup
* chore: cleanup
* chore: cleanup
* fix: disable quantize_moe_expert on merge per comment
* chore: add kernel info to optimizations doc
