Resolves conflicts in:
- vllm_omni/diffusion/registry.py: keep both LancePipeline (HEAD)
and MingImagePipeline (main) entries.
- vllm_omni/diffusion/models/bagel/bagel_transformer.py: take main's
simpler cfg_batched payload; HEAD referenced undefined locals.
Also strips vllm_omni/deploy/lance.yaml -- Lance is single-stage
diffusion, so its engine knobs (pipeline=lance, enforce_eager,
trust_remote_code, max_num_seqs=1, ...) flow directly to Omni(...)
/ vllm-omni serve instead of through a deploy YAML.
create_default_diffusion builds the stage config from those kwargs.
Touched: examples/offline_inference/lance/{end2end,gradio_demo}.py,
tests/e2e/online_serving/test_lance.py, tests/helpers/stage_config.py.
Signed-off-by: lishunyang12 <lishunyang12@163.com>
Adds Lance (bytedance-research/Lance), a 3B unified AR+diffusion
multimodal model on a Qwen2.5-VL backbone. Lance is BAGEL-lineage:
it reuses vLLM-Omni's BAGEL Mixture-of-Transformers core verbatim and
specializes only the ViT (Qwen2.5-VL vision), the VAE (Wan2.2) and the
checkpoint layout.
All six single-stage Lance modalities verified end-to-end on 1x B300:
t2i, t2v, image_edit, video_edit, x2t_image (image understanding) and
x2t_video (video understanding). 3-D mRoPE is wired through
BagelRotaryEmbedding for the x2t / video / edit paths. Includes the
upstream gap-analysis quality fixes (task-specific system prompts, full
Qwen chat template, upstream inference defaults and aspect-ratio
buckets).
Ships an offline example (examples/offline_inference/lance/), an
OpenAI-compatible online-serving example
(examples/online_serving/lance/) and an e2e test
(tests/e2e/online_serving/test_lance.py).
See LANCE_PR.md for the architecture rationale, per-modality status and
the two remaining follow-ups (two-stage AR+DiT, video_edit polish).
Closes#3697.
Signed-off-by: lishunyang <lishunyang03@gmail.com>
lishunyang12