Commit Graph

9 Commits

Author SHA1 Message Date
Wing Lian
e4032fc90f Refactor separate attention flags with attn_implementation and capability/concerns feature flags (#3602)
* upgrade to torchao 0.17.0

* chore: lint

* refactor attention handling

* replace legacy attention boolean flags with capability properties

Replace checks with capability-based properties derived from attn_implementation

This separates three concerns that were conflated under flash_attention:
1. Backend selection -> attn_implementation enum
2. Packing capability -> attn_supports_packing property
3. Flash-attn library dependency -> attn_uses_flash_lib property

* compute attn capability flags in normalizer instead of properties

* make attn_implementation the single source of truth

* move attention-dependent validators to mode=after

* migrate remaining consumers to canonical attn_implementation

* expand attention tests + rewrite docs

* migrate example configs to canonical attn_implementation

* update doc snippets + reject gemma4-hybrid with non-FA2 backend

* remove dead gemma4 branch in _set_attention_config

* fix duplicate attn_implementation in gpt-oss yamls and flaky caplog tests

* drop "Phase 2" naming from attn-implementation tests

* regroup attn_implementation tests by feature concern

* clean up verbose comments and remove MD

Signed-off-by: Wing Lian <wing@axolotl.ai>
Co-authored-by: Axolotl Swarm <no-reply@axolotl.ai>

* fix(collator): pass return_dict=True at apply_chat_template top level for transformers 5.x

In transformers 5.x, ProcessorMixin.apply_chat_template gained its own
`return_dict` parameter (defaulting to False).  When return_dict=False
and tokenize=True the method returns out["input_ids"] directly — a 2-D
tensor — rather than the full BatchFeature dict.

The old code placed `return_dict=True` inside processor_kwargs.  In
transformers 5.x those kwargs are forwarded to the underlying processor
call self(...) where _merge_kwargs silently ignores any key not present
in MllamaProcessorKwargs (emitting a warning).  The outer return_dict
therefore stayed False, apply_chat_template returned the raw input_ids
tensor, and the subsequent `batch["input_ids"]` attempted to index a
2-D tensor with the 9-character string "input_ids", producing:

  IndexError: too many indices for tensor of dimension 2

The fix is to pass return_dict=True as a top-level keyword argument to
apply_chat_template (where it is actually consumed) and remove it from
processor_kwargs (where it was silently dropped).  No version guard is
needed: transformers is pinned to ==5.5.4 in pyproject.toml.

Adds a unit-level regression test (tests/test_mm_chat_collator.py) that
mocks the processor to return a raw tensor when apply_chat_template is
called without top-level return_dict=True, verifying the four invariants:
process_rows returns a dict, input_ids is 2-D, labels is 2-D, and
apply_chat_template receives return_dict=True as a top-level kwarg.

Fixes: tests/e2e/test_llama_vision.py::TestLlamaVision::test_lora_llama_vision_multimodal_dataset
Fixes: tests/e2e/test_llama_vision.py::TestLlamaVision::test_lora_llama_vision_text_only_dataset
Signed-off-by: Wing Lian <wing@axolotl.ai>
Co-authored-by: Axolotl Swarm <no-reply@axolotl.ai>

* fix(collator): process_rows returns dict (BatchFeature) shape

Two related changes for the multimodal chat collator under transformers 5.x:

1. Wrap apply_chat_template result in dict(...) so process_rows returns
   a plain dict rather than a BatchFeature instance. BatchFeature is a
   Mapping but not a dict; downstream code that did
     batch["labels"] = self.processing_strategy.process_labels(batch["input_ids"])
   would index on a tensor when the result wasn't dict-shaped, raising
     IndexError: too many indices for tensor of dimension 2

2. Soften the regression test's contract from `dict` to `Mapping` so it
   exercises the actual semantic guarantee (key/value access) rather
   than the implementation detail (dict vs BatchFeature). Test guards
   against the original transformers 5.x breakage where apply_chat_template's
   return_dict default went from True to False.

Includes regression test under tests/test_mm_chat_collator.py.

Bug surfaced via swarm dispatch task_01KQHPNAYD8XARSNSDJVW1GPF6 against
attn-implementation-refactor; squash-merged from agent commits 4de886fd
+ dc9fcf4f.

Signed-off-by: Wing Lian <wing@axolotl.ai>

---------

Signed-off-by: Wing Lian <wing@axolotl.ai>
Co-authored-by: Axolotl Swarm <no-reply@axolotl.ai>
2026-05-05 10:15:18 -04:00
NanoCode012
17fc747f99 fix: docker build failing (#3622)
* fix: uv leftover docs

* fix: docker build failing

* chore: doc

* fix: remove old pytorch build

* fix: stop recommend flash-attn optional, let transformers pull

* fix: remove ring flash attention from image

* fix: quotes [skip ci]

* chore: naming [skip ci]
2026-04-24 14:23:09 +07:00
NanoCode012
9de5b76336 feat: move to uv first (#3545)
* feat: move to uv first

* fix: update doc to uv first

* fix: merge dev/tests into uv pyproject

* fix: update docker docs to match current config

* fix: migrate examples to readme

* fix: add llmcompressor to conflict

* feat: rec uv sync with lockfile for dev/ci

* fix: update docker docs to clarify how to use uv images

* chore: docs

* fix: use system python, no venv

* fix: set backend cpu

* fix: only set for installing pytorch step

* fix: remove unsloth kernel and installs

* fix: remove U in tests

* fix: set backend in deps too

* chore: test

* chore: comments

* fix: attempt to lock torch

* fix: workaround torch cuda and not upgraded

* fix: forgot to push

* fix: missed source

* fix: nightly upstream loralinear config

* fix: nightly phi3 long rope not work

* fix: forgot commit

* fix: test phi3 template change

* fix: no more requirements

* fix: carry over changes from new requirements to pyproject

* chore: remove lockfile per discussion

* fix: set match-runtime

* fix: remove unneeded hf hub buildtime

* fix: duplicate cache delete on nightly

* fix: torchvision being overridden

* fix: migrate to uv images

* fix: leftover from merge

* fix: simplify base readme

* fix: update assertion message to be clearer

* chore: docs

* fix: change fallback for cicd script

* fix: match against main exactly

* fix: peft 0.19.1 change

* fix: e2e test

* fix: ci

* fix: e2e test
2026-04-21 10:16:03 -04:00
Wing Lian
a531e9d946 upgrade vllm to v0.14.0 (#3345) 2026-01-21 20:00:18 -05:00
NanoCode012
9901ee5602 fix: voxtralprocessor broken (#3255) [skip ci]
* fix: voxtralprocessor broken

* chore: add todo

* chore: wording
2025-11-13 10:18:42 -05:00
NanoCode012
09959fac70 Feat: add Magistral Small 2509 and native mistral3 tokenizer support (#3165)
* feat: update mistral common

* feat: add mistral3processor

* fix: loading

* fix: cast pixel_values to fp32

* fix: image tensor conversion

* feat: add FA2 support for pixtral based models

* fix: update mistral small 3.1 to use native tokenizer

* fix: install tips

* fix: improve info on sample dataset files

* chore: move mistral configs into subfolders

* fix: remove unneeded patch

* fix: indent

* feat: add integration tests

* chore: move

* feat: add magistral 2509 docs and example

* fix: convert tensor to bool

* feat: expand tests

* chore: move tests
2025-09-18 15:42:20 +07:00
NanoCode012
b71482cec5 Feat: add hunyuan v1 (#3016)
* feat: add hunyuan cce support

* feat: update cce docs

* feat: add multipack support for granite and hunyuan

* feat: add hunyuan docs and example config

* feat: update readme instructions to include CCE installation

* fix: chat template log appearing despite tokenizer already having template

* feat: add vram usage

* fix: remove duplicate cce install

* fix: use latest commit of PR in case rebased/pushed

* Revert "fix: use latest commit of PR in case rebased/pushed"

This reverts commit 8b60aa00de.

* feat: update doc as upstream merged
2025-09-10 09:03:30 +07:00
NanoCode012
4db7f023c6 feat(doc): standardize the axolotl install to a release (#3040) [skip ci] 2025-08-08 08:00:26 -04:00
NanoCode012
90e5598930 Feat: Add voxtral, magistral small 1.1, and misc gemma3n fixes (#2979)
* fix: lock version in gemma3n docs

* feat: add sample configs and docs

* chore: move mistraltokenizer into mistral folder

* feat: update instructions

* feat: add dynamic load voxtral

* fix: remove incorrect vision config, add audio

* fix: support voxtral processing strategy and address none in data

* feat: patch mistraltokenizer subclass upstream and add missing

* feat: update cce commit to include voxtral

* fix: remove old comment

* fix: gemma3 patch not needed anymore

* fix: voxtral modeling code

* fix: remove incorrect ds path

* fix: adjust apply chat template parsing

* feat: enable voxtral patch

* fix: patch

* feat: update example datasets

* fix: target layer

* feat: update gemma3n docs

* feat: update voxtral docs

* feat: revert assistant parsing to rely on new upstream changes

* chore: skip test till next PR fix

* fix: override upstream decode due to missing handling

* feat: update readme

* fix: update

* feat: add magistral small think support

* feat: update mistral-common dep

* fix: lint

* fix: remove optional dep

* chore: typing

* chore: simply import

* feat(doc): update differences for 2507

* fix: coderrabbit comments

* feat: update clarify docs on new transformers
2025-07-30 15:57:05 +07:00