The pair for vLLM v0.29.0: rc1's docs pin vllm==0.29.0 and a static scan of
rc1's vllm.* imports against the v0.29.0 tree finds nothing missing, while
our 0.28-based tree needs seven modules v0.29.0 no longer has
(vllm.inputs.preprocess, entrypoints.launcher, openai.cli_args,
openai.engine.protocol, serve.utils.server_utils, layers.batch_invariant,
models.hunyuan_v1).
Ten files conflicted. Upstream's structure is the base everywhere; the
fork's features are re-attached to it:
- deploy_profile / apply_deploy_profile run before rc1's resolve_omni_config
pops deploy_config (async_omni_engine, cli/serve); the deploy-profile
selector and the resolve_model_config_path chain it needs stay in
entrypoints/utils.py; stage_overrides takes rc1's dict type.
- config_factory keeps the lazy diffusion output-type import; the diffusion
registry import in rc1's new config/resolver.py is made lazy for the same
WP6 reason (TTS path must not load diffusion).
- requirements: our core/media split kept; rc1's transformers>=5.13 floor
and kernels==0.16.1 applied in core.txt / media.txt.
- TTS: rc1's split_granularity and bounded seed plus our output_mode=
codec_tokens, _SessionInbox cancel handling and codec DELTA accumulation;
our private _conditioning_cache_salt is superseded by rc1's public
tts_adapters/base.py::conditioning_cache_salt.
- stage_runtime: rc1's single ExitStack G2 path (lock released before READY)
replaces our two-path block, with the four worker_phase names the init
profiler consumes still emitted; _cpu_placed / host admission kept.
Not yet run against vLLM 0.29.0: the tests listed in the W6 record.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Verbatim copy of the edge/omni-edge working tree (tracked diffs + untracked
edge/local, tests/edge/local, docs/edge, pipeline files). Taken so that
vLLM-Omni v0.29.0rc1 can be merged on a branch without touching the
user's working tree. logs_edge/ and benchmark .npy outputs excluded.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
`vllm_omni/deploy/edge/qwen3_tts.yaml` carries `orchestrator:
parallel_stage_init: true`, but `_apply_profile_orchestrator_defaults` ran
only on the `deploy_profile` path. Pointing `--deploy-config` at the same file
loaded its stages and silently dropped the block, so the edge deployment
started sequentially:
--deploy-profile edge 30.76 s
--deploy-config .../edge/qwen3_tts.yaml 63.76 s (same file)
with nothing in the log to say why. The block now applies however the config
was reached. Explicit arguments still win, and the allow-list stays narrow --
a test checks an unrecognised key cannot be injected through it.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Two corrections and the paperwork they imply.
The fused-RMSNorm registration defaulted to *on*, which contradicts the
measurement it was committed with: those kernels are 3.6x and 4.5x faster in
isolation but measured 72.7 tok/s against 74.0 end to end, because inductor
already fuses the native norm into the residual add and an opaque call breaks
that fusion. The implementations stay registered, so the provider remains
selectable through `kernel_config.ir_op_priority` on a machine where the trade
lands differently; only the default ranking is left alone now, and the test
asserts both states rather than just the opt-in one.
The four switches this branch added (VLLM_OMNI_AOT_CACHE_SHIM,
_CPU_FUSED_NORMS, _CPU_RELEASE_MEMORY, _SPARK_GATE_REDUCTION) were not in the
reviewed environment-variable inventory, so
`test_statically_resolvable_environment_accesses_are_classified` failed. They
are classified now, the reviewed count moves 28 -> 32 with a note saying why,
and each has a row in docs/configuration/environment_variables.md carrying the
measurement that justifies its default.
`VLLM_OMNI_CPU_FAST_SAMPLER` and `VLLM_OMNI_STEP_STATS_SYNC` remain
unclassified and that test still fails on them. They arrived in 6ce8de1b, in
files this branch does not touch, so they are left to whoever owns that work
rather than documented from a guess.
Under `-m "core_model and cpu"`: 2593 passed before these fixes with 9
failures, of which two were mine. The rest are CUDA-only tests in a CPU venv
("Torch not compiled with CUDA enabled") plus test_qnn_export.py, which
another session is actively editing.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
- environment_variable_inventory: VLLM_OMNI_CPU_INDUCTOR / HW_PROFILE /
INIT_TIMELINE / STEP_STATS_DIR (public), STAGE_ID / INIT_TIMELINE_DIR
(internal); reference page rows added.
- edge_decoder_client.LocalDecoder: batched_chunked_decode takes a [B, Q, F]
tensor, not a list (the WP5 e2e run failed with a TypeError); the decoder
now also carries the ramp schedule attributes the Code2Wav stage sets.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
- vllm_omni/edge/step_stats.py: process-local counters enabled by
VLLM_OMNI_STEP_STATS_DIR (scheduler schedule/update_from_output, engine-core
step, chunk hop enqueue->put / put->get / get, orchestrator dispatch), dumped
per process and merged into an attribution table (share of the 80 ms frame).
Hooks: stage_engine_core_proc (instrument after construction, dump at exit),
chunk_transfer_adapter (put/get timing, put->get via the shm lock-file mtime),
orchestrator dispatch loop. Bench: stream_latency_bench.py --step-stats.
- vllm_omni/edge/scheduling.py: playback slack, prefill-throttle decision and
the no-preemption KV admission rule (exact bytes/token from the talker KV
geometry); adapt.derive_overrides now sizes max_num_seqs with it and
auto_profile passes the geometry read from the model config.
- Engine re-reads parallel_stage_init after apply_deploy_profile so the edge
profile's orchestrator default takes effect (was read before the profile).
- benchmarks/tts/cpu_thread_sweep.py: CPU-only 8/16/32-thread sweep (+inductor)
with per-step attribution.
- Tests: tests/core/test_edge_scheduling.py, tests/edge/test_step_stats.py,
tests/benchmarks/test_cpu_thread_sweep.py, profile default test.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
* diffusers is no longer imported by vllm_omni.diffusion.data (annotation only);
vllm_omni.diffusion.io_support (diffusion registry + distributed state) is
imported lazily by config_factory and async_omni_engine, so constructing a
Qwen3-TTS pipeline config / AsyncOmni no longer loads diffusers,
x_transformers or whisper (guarded by tests/config/test_import_guard.py).
* requirements/common.txt = core.txt (AR/speech runtime) + media.txt
(diffusion/video/extra audio); VLLM_OMNI_EDGE_BUILD=1 makes setup.py use
requirements/<device>-edge.txt (core only); `edge` extra adds websockets and
sounddevice for on-device clients.
Measured on this host (CUDA venv): `import vllm` 7.0-7.9 s, `import vllm_omni`
adds ~20 s of which ~17 s is transformers' own import (transformers.utils.import_utils)
pulled in by vllm_omni.patch / vllm_omni.version; that floor is not
vLLM-Omni's and is unchanged. Guard test: no diffusion module loaded on the TTS path.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
* vllm_omni/deploy/edge/qwen3_tts.yaml: single-device Qwen3-TTS profile with a
ramped codec chunk schedule (2->4->8->16->25 frames) that removes the ~80 ms
playback stall of the default 1->25 schedule, decode batch 1, max_num_seqs 4.
* deploy_profile="edge" (Omni/AsyncOmni kwarg, --deploy-profile CLI, headless
serve) resolves vllm_omni/deploy/<profile>/<model_type>.yaml; mutually
exclusive with deploy_config; explicit profiles never fall back silently.
* tests/helpers/stage_config.py: modify_stage_config anchors a relative
base_config before writing the temp YAML so overlay-derived configs resolve.
* async_omni_engine.py also carries the init-timeline hooks used by WP2.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
