From 10221f0665cd5930f031008d2cec98704d33ad93 Mon Sep 17 00:00:00 2001 From: tzhouam Date: Wed, 23 Sep 2026 17:44:02 +0800 Subject: [PATCH] Qualify scoped MiniCPM-o image and audio paths on WSL CPU --- .../results/e2e_expansion_20260923/README.md | 28 +- ...0_40b94cec-371c-47a8-ba61-4729a0eb1285.txt | 16 + .../minicpmo_cpu_audio.log | 250 ++++++++ .../minicpmo_cpu_audio_artifact_report.json | 15 + .../minicpmo_cpu_audio_offline.yaml | 127 ++++ ...0_40b94cec-371c-47a8-ba61-4729a0eb1285.wav | Bin 0 -> 103724 bytes ...0_54927839-1ab7-4d0d-86a3-0d6290a84f13.txt | 16 + .../minicpmo_cpu_image.log | 248 ++++++++ .../minicpmo_cpu_image_artifact_report.json | 15 + .../minicpmo_cpu_image_offline.yaml | 127 ++++ .../minicpmo_cpu_image_wrong_source.log | 555 ++++++++++++++++++ ...0_54927839-1ab7-4d0d-86a3-0d6290a84f13.wav | Bin 0 -> 249644 bytes .../evidence/summary/README.md | 4 +- docs/design/omni_edge_e2e_roadmap.md | 9 +- 14 files changed, 1404 insertions(+), 6 deletions(-) create mode 100644 benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_audio/0_40b94cec-371c-47a8-ba61-4729a0eb1285.txt create mode 100644 benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_audio/minicpmo_cpu_audio.log create mode 100644 benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_audio/minicpmo_cpu_audio_artifact_report.json create mode 100644 benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_audio/minicpmo_cpu_audio_offline.yaml create mode 100644 benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_audio/output_0_40b94cec-371c-47a8-ba61-4729a0eb1285.wav create mode 100644 benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_image/0_54927839-1ab7-4d0d-86a3-0d6290a84f13.txt create mode 100644 benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_image/minicpmo_cpu_image.log create mode 100644 benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_image/minicpmo_cpu_image_artifact_report.json create mode 100644 benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_image/minicpmo_cpu_image_offline.yaml create mode 100644 benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_image/minicpmo_cpu_image_wrong_source.log create mode 100644 benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_image/output_0_54927839-1ab7-4d0d-86a3-0d6290a84f13.wav diff --git a/benchmarks/edge_harness/results/e2e_expansion_20260923/README.md b/benchmarks/edge_harness/results/e2e_expansion_20260923/README.md index 669919380..3a7a84aca 100644 --- a/benchmarks/edge_harness/results/e2e_expansion_20260923/README.md +++ b/benchmarks/edge_harness/results/e2e_expansion_20260923/README.md @@ -1,11 +1,13 @@ # 2026-09-23 WSL CPU and native Windows expansion -This extends the [60-cell device × model matrix](../e2e_profiling_20260922/evidence/summary/README.md) with previously unrun WSL CPU and native Windows paths. The September 22 timing tables remain historical. MiniCPM-o now has separate 20-request serial text-to-speech timing runs on WSL CPU and native Windows GPU; each InternVLA timing remains one observation. None is a sustained or full-modality profile. The [checkpoint manifests](../e2e_recovery_20260923/README.md) pin the real weights. No model, precision or context was silently substituted. +This extends the [60-cell device × model matrix](../e2e_profiling_20260922/evidence/summary/README.md) with previously unrun WSL CPU and native Windows paths. The September 22 timing tables remain historical. MiniCPM-o now has separate 20-request serial text-to-speech timing runs on WSL CPU and native Windows GPU, plus one synthetic image and one synthetic audio input on each platform; each InternVLA timing remains one observation. None is a sustained or full-modality profile. The [checkpoint manifests](../e2e_recovery_20260923/README.md) pin the real weights. No model, precision or context was silently substituted. | Device / model | Verified depth | Observed output and time | Remaining gate | |---|---|---|---| -| WSL CPU / MiniCPM-o 4.5, revision `503e754207c94da6bb26850b4469f367c9ea3582` | Scoped complete three-stage text-to-text+speech path (P for this input only) | Coherent text and a 5.2 s mono 24 kHz WAV. First request 27.09 s after 73.65 s startup; separate 1-warmup/20-measured serial run: startup 73.89 s, request wall p50 21.86 s/p95 22.97 s. | Speech intelligibility/alignment, image/audio/video inputs, concurrency, interruption, power and thermal behavior. | -| Native Windows RTX 5090 Laptop / MiniCPM-o 4.5, same revision | Scoped complete three-stage text-to-text+speech path (P for this input only) | Coherent text with the same 32 thinker token IDs as WSL CUDA, and a nonzero 5.2 s mono 24 kHz WAV. First engine startup 297.20 s and request 78.75 s, including first-use graph/JIT work; separate 1-warmup/20-measured serial run: startup 239.05 s, request wall p50 18.38 s/p95 18.73 s. | Speech intelligibility/alignment, image/audio/video inputs, concurrency, interruption, loading peak and sustained behavior. | +| WSL CPU / MiniCPM-o 4.5, revision `503e754207c94da6bb26850b4469f367c9ea3582` | Scoped complete three-stage text-to-text+speech path (P for this input only) | Coherent text and a 5.2 s mono 24 kHz WAV. First request 27.09 s after 73.65 s startup; separate 1-warmup/20-measured serial run: startup 73.89 s, request wall p50 21.86 s/p95 22.97 s. | Speech intelligibility/alignment, real image/audio quality, video input, concurrency, interruption, power and thermal behavior. | +| WSL CPU / MiniCPM-o 4.5, same revision | Scoped three-stage **image**-to-text+speech path (P for one synthetic image) | For the 448×448 red square, returned a correct description and nonzero 5.2 s WAV. Startup 112.44 s; one request 37.70 s. Text and token IDs differed from WSL GPU while describing the same visible content. | Real-image suite, speech meaning, repeated latency, memory admission and clean shutdown. | +| WSL CPU / MiniCPM-o 4.5, same revision | Scoped three-stage **audio**-to-text+speech path (P for one synthetic clip) | For the 2 s, 440 Hz tone, answered “A loud and high pitched beep” and produced a nonzero 2.16 s WAV. Startup 101.22 s; one request 17.30 s. Text and token IDs differed from WSL GPU. | Real-audio and transcription suites, speech meaning, repeated latency, memory admission and clean shutdown. | +| Native Windows RTX 5090 Laptop / MiniCPM-o 4.5, same revision | Scoped complete three-stage text-to-text+speech path (P for this input only) | Coherent text with the same 32 thinker token IDs as WSL CUDA, and a nonzero 5.2 s mono 24 kHz WAV. First engine startup 297.20 s and request 78.75 s, including first-use graph/JIT work; separate 1-warmup/20-measured serial run: startup 239.05 s, request wall p50 18.38 s/p95 18.73 s. | Speech intelligibility/alignment, real image/audio quality, video input, concurrency, interruption, loading peak and sustained behavior. | | WSL RTX 5090 Laptop / MiniCPM-o 4.5, same revision | Scoped three-stage **image**-to-text+speech path (P for one synthetic image) | For a 448×448 red square on white, returned the correct visual description and a nonzero 5.2 s WAV. Engine startup 101.96 s; one request 17.49 s. | Broader visual quality, real images, audio/video inputs, speech intelligibility, repeated latency and cleanup reliability. | | WSL RTX 5090 Laptop / MiniCPM-o 4.5, same revision | Scoped three-stage **audio**-to-text+speech path (P for one synthetic clip) | For a 2 s, 440 Hz tone at 16 kHz, answered “A loud whistling sound” and produced a nonzero 2.16 s WAV. Engine startup 105.94 s; one request 7.78 s. | Speech transcription/real audio quality, video input, speech intelligibility, repeated latency and shared-memory cleanup. | | Native Windows RTX 5090 Laptop / MiniCPM-o 4.5, same revision | Scoped three-stage **image**-to-text+speech path (P for one synthetic image) | For the same 448×448 red square, returned exactly the same text and 27 thinker token IDs as WSL CUDA, plus a nonzero 5.2 s WAV. Engine startup 334.16 s; one request 17.15 s. | Real-image quality, audio/video inputs, speech intelligibility, repeated latency, memory and sustained behavior. | @@ -18,6 +20,8 @@ Both runs used Ryzen AI 9 HX 370 on Ubuntu 26.04/WSL2 kernel `6.18.33.2-microsof The separate [20-request profile](evidence/minicpmo/minicpmo_cpu_profile_20.json) records every measured output and sampled memory; the [JSONL](evidence/minicpmo/minicpmo_cpu_profile_20.jsonl) survives interruption, and the [run log](evidence/minicpmo/minicpmo_cpu_profile_20.log) retains worker details. One warmup was excluded. All 20 measured requests returned the same thinker token sequence, nonzero 124,800-sample audio, and request wall times 20.95–23.33 s; nearest-rank p50/p95 were 21.86/22.97 s (real-time factor 4.20/4.42 for 5.2 s of audio). Sampled WSL available RAM reached a minimum of 3.80 GB and swap use a maximum of 5.75 GB; summed process-tree RSS reached 29.04 GB but double-counts shared pages. These are 0.5 s samples during requests, not load-peak or unique-resident-memory measurements. Audio and text were returned together at request completion, so the profile cannot establish playable-stream latency, and no concurrency or 30-minute thermal run was performed. +The WSL CPU image and audio runs reused the same real checkpoint, BF16 three-stage plan, eager execution, 2,048/512-token limits, 1 GiB CPU KV cache per stage and `OMP_NUM_THREADS=8` as the CPU text run. Their [image plan](evidence/minicpmo_wsl_cpu_image/minicpmo_cpu_image_offline.yaml) and [audio plan](evidence/minicpmo_wsl_cpu_audio/minicpmo_cpu_audio_offline.yaml) each admit only the named input. They used the same [red-square image](evidence/minicpmo_wsl_image/red_square.png) and [440 Hz tone](evidence/minicpmo_wsl_audio/tone_440hz_2s_16khz.wav) as the GPU runs. The image [raw log](evidence/minicpmo_wsl_cpu_image/minicpmo_cpu_image.log), [text/token IDs](evidence/minicpmo_wsl_cpu_image/0_54927839-1ab7-4d0d-86a3-0d6290a84f13.txt), [WAV](evidence/minicpmo_wsl_cpu_image/output_0_54927839-1ab7-4d0d-86a3-0d6290a84f13.wav) and [artifact report](evidence/minicpmo_wsl_cpu_image/minicpmo_cpu_image_artifact_report.json) show a correct visual description and a nonzero 124,800-frame, 24 kHz WAV. The audio [raw log](evidence/minicpmo_wsl_cpu_audio/minicpmo_cpu_audio.log), [text/token IDs](evidence/minicpmo_wsl_cpu_audio/0_40b94cec-371c-47a8-ba61-4729a0eb1285.txt), [WAV](evidence/minicpmo_wsl_cpu_audio/output_0_40b94cec-371c-47a8-ba61-4729a0eb1285.wav) and [artifact report](evidence/minicpmo_wsl_cpu_audio/minicpmo_cpu_audio_artifact_report.json) show a plausible tone description and a nonzero 51,840-frame, 24 kHz WAV. CPU text and token IDs differ from GPU for both inputs; no reference-quality threshold was applied. Each run force-killed stage 0 at shutdown and reported shared-memory cleanup warnings. Manual `free -h` snapshots during startup/request showed swap around 5.3 GiB for image and 4.1 GiB for audio, but these are neither load peaks nor model-attributed memory measurements. The first image attempt [failed](evidence/minicpmo_wsl_cpu_image/minicpmo_cpu_image_wrong_source.log) because the CPU venv loaded an older editable Omni checkout lacking the existing `cosyvoice2` YAML compatibility fix; setting `PYTHONPATH` explicitly to this checkout corrected the source path. This is a setup failure, not a model-input failure. + Native Windows MiniCPM-o used the same [constrained CUDA deployment config](../e2e_recovery_20260923/evidence/minicpmo/minicpmo_24gb_offline.yaml) as the WSL CUDA run: BF16, eager vLLM 0.29.0, 2,048-token thinker / 512-token talker limits, text input only, one request and 5 GiB thinker host offload. The local Windows 11 build 26200 host has 63.12 GiB visible RAM, an RTX 5090 Laptop GPU (driver 610.71), Python 3.12.10, PyTorch 2.13.0+cu130, Transformers 5.14.1, `stepaudio2-minicpmo` 0.1.1 and `pyarrow` 25.0.1. The checkpoint was read through a local WSL UNC path. The example's then-default 300 s overall startup timeout [expired](evidence/minicpmo_windows/minicpmo_native_gpu.log) after stage initialization had nearly completed; rerunning with `--init-timeout 900 --stage-init-timeout 600` [completed](evidence/minicpmo_windows/minicpmo_native_gpu_timeout900.log) in 297.20 s startup and one 78.75 s request. The example default has since been raised to 600 s, matching Omni's default. The text [and token IDs](evidence/minicpmo_windows/0_b4835d8d-f4f8-48b9-85d2-bb7ef06d9249.txt) exactly match the WSL CUDA result. The [WAV](evidence/minicpmo_windows/output_0_b4835d8d-f4f8-48b9-85d2-bb7ef06d9249.wav) has 124,800 mono PCM16 frames at 24 kHz; 124,560 samples are nonzero. The [artifact report](evidence/minicpmo_windows/minicpmo_windows_artifact_report.json) records its checksum and signal statistics. One first-use request is not a latency distribution or speech-quality assessment; the distinct Windows timing must not be transferred to WSL or CPU. The separate native Windows [20-request profile](evidence/minicpmo_windows/minicpmo_windows_gpu_profile20.json), [per-request JSONL](evidence/minicpmo_windows/minicpmo_windows_gpu_profile20.jsonl), and [raw log](evidence/minicpmo_windows/minicpmo_windows_gpu_profile20.log) used one warmup followed by 20 measured serial requests in one engine. All measured requests returned one consistent thinker token sequence and 124,800-sample audio with nonzero RMS. Nearest-rank request wall p50/p95 were 18.38/18.73 s (real-time factor 3.53/3.60 for 5.2 s of audio), with observed range 18.22–19.79 s. Engine startup was 239.05 s on this later, warm-filesystem run. During measured requests, 0.5 s samples found native host available RAM as low as 0.78 GB and pagefile use as high as 11.17 GB; summed process-tree RSS reached 21.08 GB but double-counts shared pages. These are host-wide samples, not model-only RAM or loading peak. Neither a playable-stream timing nor speech intelligibility, concurrency, interruption, power or a 30-minute thermal run was measured. @@ -57,6 +61,24 @@ export CUDA_VISIBLE_DEVICES= VLLM_TARGET_DEVICE=cpu VLLM_CPU_KVCACHE_SPACE=1 VLL --deploy-config benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo/minicpmo_cpu_offline.yaml \ --warmups 1 --repeats 20 --output /tmp/minicpmo-cpu-profile-20.json +# Pin this checkout: the CPU venv also contains an older editable Omni checkout. +export PYTHONPATH=/home/zhout/project/edge_infer/vllm-omni-edge +/home/zhout/project/edge_infer/.venvs/omni-cpu/bin/python examples/offline_inference/minicpmo/end2end.py \ + --model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5 \ + --deploy-config benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_image/minicpmo_cpu_image_offline.yaml \ + --query-type use_image \ + --image-path benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_image/red_square.png \ + --modalities text,audio --num-prompts 1 --init-timeout 900 --stage-init-timeout 600 \ + --output-dir /tmp/minicpmo-wsl-cpu-image + +/home/zhout/project/edge_infer/.venvs/omni-cpu/bin/python examples/offline_inference/minicpmo/end2end.py \ + --model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5 \ + --deploy-config benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_audio/minicpmo_cpu_audio_offline.yaml \ + --query-type use_audio \ + --audio-path benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_audio/tone_440hz_2s_16khz.wav \ + --modalities text,audio --num-prompts 1 --init-timeout 900 --stage-init-timeout 600 \ + --output-dir /tmp/minicpmo-wsl-cpu-audio + CUDA_VISIBLE_DEVICES=0 VLLM_TARGET_DEVICE=cuda VLLM_USE_FLASHINFER_SAMPLER=0 \ /home/zhout/project/edge_infer/.venvs/omni-cuda-029/bin/python examples/offline_inference/minicpmo/end2end.py \ --model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5 \ diff --git a/benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_audio/0_40b94cec-371c-47a8-ba61-4729a0eb1285.txt b/benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_audio/0_40b94cec-371c-47a8-ba61-4729a0eb1285.txt new file mode 100644 index 000000000..199e27a35 --- /dev/null +++ b/benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_audio/0_40b94cec-371c-47a8-ba61-4729a0eb1285.txt @@ -0,0 +1,16 @@ +Prompt: +<|im_start|>system +You are MiniCPM-o, a helpful multimodal assistant that can understand images, audio and video, and respond in text and speech.<|im_end|> +<|im_start|>user +() +What is the content of this audio?<|im_end|> +<|im_start|>assistant + + + + +<|tts_bos|> +vllm_text_output: +A loud and high pitched beep. +vllm_token_ids: +[32, 17361, 323, 1550, 48998, 90954, 13, 151704, 151645] diff --git a/benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_audio/minicpmo_cpu_audio.log b/benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_audio/minicpmo_cpu_audio.log new file mode 100644 index 000000000..f6dce1895 --- /dev/null +++ b/benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_audio/minicpmo_cpu_audio.log @@ -0,0 +1,250 @@ +W0923 17:38:24.658000 2302365 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +W0923 17:38:24.703000 2302365 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +WARNING 09-23 17:38:26 [importing.py:65] Triton is installed, but doesn't include CPU backend. Disabling Triton. +INFO 09-23 17:38:26 [importing.py:88] Triton not installed or not compatible; certain GPU-related functions will not be available. +/home/zhout/project/edge_infer/vllm-omni-edge/vllm_omni/version.py:55: RuntimeWarning: vLLM and vLLM-Omni appear to have mismatched major/minor versions: + --> vLLM-Omni version 0.29.0rc2.dev71+g00510ce38.d20260922 + --> vLLM version 0.28.0 +This will likely cause compatibility issues. + warn_if_misaligned_vllm_version() +INFO 09-23 17:38:27 [patch.py:259] NVFP4 W4A4 weight_scale NaN-clamp: installed. +INFO 09-23 17:38:28 [patch.py:510] inductor factorable-divisibility patch: installed. +INFO 09-23 17:38:28 [patch.py:646] CPU AOT compile-cache load shim installed: compiled models are reused across engine starts instead of being recompiled. +INFO 09-23 17:38:28 [patch.py:756] CPU weight-load memory release installed (set VLLM_OMNI_CPU_RELEASE_MEMORY=0 to disable). +==================== + vllm version: 0.28.0 + ==================== +INFO 09-23 17:38:28 [omni_base.py:216] [Omni] Initializing with model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5 +INFO 09-23 17:38:28 [async_omni_engine.py:172] [AsyncOmniEngine] Initializing with model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5 +INFO 09-23 17:38:28 [async_omni_engine.py:290] [AsyncOmniEngine] Launching Orchestrator thread with 3 stages +INFO 09-23 17:38:28 [stage_init_utils.py:768] [stage_init] Set VLLM_WORKER_MULTIPROC_METHOD=spawn +INFO 09-23 17:38:28 [initialization.py:356] Loaded OmniTransferConfig with 1 connector configurations +WARNING 09-23 17:38:28 [utils.py:501] Dropping unknown OmniEngineArgs field 'inline_diffusion' (not declared on the dataclass) +WARNING 09-23 17:38:28 [utils.py:501] Dropping unknown OmniEngineArgs field 'shm_threshold_bytes' (not declared on the dataclass) +WARNING 09-23 17:38:28 [arg_utils.py:1719] The global random seed is set to 0. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. +INFO 09-23 17:38:29 [model.py:672] Resolved architecture: MiniCPMO45OmniForConditionalGeneration +INFO 09-23 17:38:29 [model.py:1965] Using max model len 2048 +WARNING 09-23 17:38:29 [model.py:963] Model does not support mm_device_do_normalize, forcing mm_device_do_normalize = False. +INFO 09-23 17:38:29 [scheduler.py:242] Chunked prefill is enabled with max_num_batched_tokens=2048. +WARNING 09-23 17:38:29 [vllm.py:1285] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none +WARNING 09-23 17:38:29 [vllm.py:1354] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. +INFO 09-23 17:38:29 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +WARNING 09-23 17:38:29 [vllm.py:652] Model Runner V2 requires Triton; using the V1 model runner instead. +INFO 09-23 17:38:29 [compilation.py:329] Enabled custom fusions: norm_quant, act_quant +WARNING 09-23 17:38:29 [utils.py:501] Dropping unknown OmniEngineArgs field 'inline_diffusion' (not declared on the dataclass) +WARNING 09-23 17:38:29 [utils.py:501] Dropping unknown OmniEngineArgs field 'shm_threshold_bytes' (not declared on the dataclass) +WARNING 09-23 17:38:29 [arg_utils.py:1719] The global random seed is set to 0. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. +INFO 09-23 17:38:29 [model.py:672] Resolved architecture: MiniCPMO45OmniForConditionalGeneration +INFO 09-23 17:38:29 [model.py:1965] Using max model len 512 +WARNING 09-23 17:38:29 [model.py:963] Model does not support mm_device_do_normalize, forcing mm_device_do_normalize = False. +INFO 09-23 17:38:29 [model.py:1965] Using max model len 512 +INFO 09-23 17:38:29 [scheduler.py:242] Chunked prefill is enabled with max_num_batched_tokens=512. +INFO 09-23 17:38:29 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +WARNING 09-23 17:38:29 [utils.py:501] Dropping unknown OmniEngineArgs field 'inline_diffusion' (not declared on the dataclass) +WARNING 09-23 17:38:29 [utils.py:501] Dropping unknown OmniEngineArgs field 'shm_threshold_bytes' (not declared on the dataclass) +WARNING 09-23 17:38:29 [arg_utils.py:1719] The global random seed is set to 0. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. +INFO 09-23 17:38:29 [model.py:672] Resolved architecture: MiniCPMO45Code2Wav +INFO 09-23 17:38:29 [model.py:1965] Using max model len 4096 +WARNING 09-23 17:38:29 [arg_utils.py:2664] This model does not officially support disabling chunked prefill. Disabling this manually may cause the engine to crash or produce incorrect outputs. +INFO 09-23 17:38:29 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +INFO 09-23 17:38:29 [stage_runtime.py:853] [stage_init] Stage-0 set runtime devices: 0 +W0923 17:38:33.734000 2302392 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +W0923 17:38:33.766000 2302392 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +WARNING 09-23 17:38:34 [importing.py:65] Triton is installed, but doesn't include CPU backend. Disabling Triton. +INFO 09-23 17:38:34 [importing.py:88] Triton not installed or not compatible; certain GPU-related functions will not be available. +/home/zhout/project/edge_infer/vllm-omni-edge/vllm_omni/version.py:55: RuntimeWarning: vLLM and vLLM-Omni appear to have mismatched major/minor versions: + --> vLLM-Omni version 0.29.0rc2.dev71+g00510ce38.d20260922 + --> vLLM version 0.28.0 +This will likely cause compatibility issues. + warn_if_misaligned_vllm_version() +INFO 09-23 17:38:35 [patch.py:259] NVFP4 W4A4 weight_scale NaN-clamp: installed. +INFO 09-23 17:38:36 [patch.py:510] inductor factorable-divisibility patch: installed. +INFO 09-23 17:38:36 [patch.py:646] CPU AOT compile-cache load shim installed: compiled models are reused across engine starts instead of being recompiled. +INFO 09-23 17:38:36 [patch.py:756] CPU weight-load memory release installed (set VLLM_OMNI_CPU_RELEASE_MEMORY=0 to disable). +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:38:36 [core.py:122] Initializing a V1 LLM engine (v0.28.0) with config: model='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', speculative_config=None, tokenizer='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=2048, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=None, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False, jit_monitor_mode='warn', jit_monitor_verbose=False), seed=0, served_model_name=/home/zhout/project/edge_infer/models/MiniCPM-o-4_5, enable_prefix_caching=False, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_vision_items_per_batch': 0, 'encoder_cudagraph_max_frames_per_batch': None, 'compile_sizes': None, 'compile_ranges_endpoints': [2048], 'inductor_compile_config': {'enable_auto_functionalized_v2': False}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'enable_qk_norm_rope_fusion': False, 'fuse_rope_kvcache_cat_mla': False, 'fuse_act_padding': False, 'fuse_qk_norm_rope_kvcache': False}, 'max_cudagraph_capture_size': None, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']), enable_flashinfer_autotune=True, enable_cutedsl_warmup=True, enable_jit_warmup=True, enable_bf16x3_router_gemm=False, moe_backend='auto', linear_backend='auto') +[W923 17:38:37.553020102 utils.cpp:68] Warning: NUMA binding: Using MEMBIND policy for memory allocation on the NUMA nodes (0). Memory allocations will be strictly bound to these NUMA nodes. (function init_cpu_memory_env) +(StageEngineCoreProc_stage0_replica0 pid=2302392) WARNING 09-23 17:38:37 [vllm.py:652] Model Runner V2 requires Triton; using the V1 model runner instead. +(StageEngineCoreProc_stage0_replica0 pid=2302392) WARNING 09-23 17:38:37 [cpu_worker.py:127] libiomp is not found in LD_PRELOAD. For best performance, please follow the section `set LD_PRELOAD` in https://docs.vllm.ai/en/latest/getting_started/installation/cpu/ to setup required pre-loaded libraries. +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:38:37 [parallel_state.py:1638] world_size=1 rank=0 local_rank=0 distributed_init_method=file:///tmp/vllm_dist_206b084e83e74e7ea4e80136de239ff3 backend=gloo +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:38:37 [parallel_state.py:1982] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A, EPLB rank N/A +(StageEngineCoreProc_stage0_replica0 pid=2302392) WARNING 09-23 17:38:37 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2302392) [transformers] `MiniCPMOProcessor` defines `image_processor_class = 'AutoImageProcessor'`, which is deprecated. Register the correct mapping in `AutoImageProcessor` instead. +(StageEngineCoreProc_stage0_replica0 pid=2302392) [transformers] Requested torchvision backend is not available. Falling back to pil backend. +(StageEngineCoreProc_stage0_replica0 pid=2302392) [transformers] `MiniCPMOProcessor` defines `feature_extractor_class = 'WhisperFeatureExtractor'`, which is deprecated. Register the correct mapping in `AutoFeatureExtractor` instead. +(StageEngineCoreProc_stage0_replica0 pid=2302392) WARNING 09-23 17:38:43 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2302392) WARNING 09-23 17:38:43 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2302392) WARNING 09-23 17:38:43 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:38:43 [cpu_model_runner.py:131] Starting to load model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5... +(StageEngineCoreProc_stage0_replica0 pid=2302392) WARNING 09-23 17:38:43 [vllm.py:1285] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none +(StageEngineCoreProc_stage0_replica0 pid=2302392) WARNING 09-23 17:38:43 [vllm.py:1354] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:38:43 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:38:43 [compilation.py:329] Enabled custom fusions: norm_quant, act_quant +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:38:43 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:38:43 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:38:43 [selector.py:217] Using HND KV cache layout for CPU_ATTN backend. +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:38:47 [weight_utils.py:858] Filesystem type for checkpoints: EXT4. Checkpoint size: 17.46 GiB. Available RAM: 27.00 GiB. +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:38:47 [weight_utils.py:881] Auto-prefetch is disabled because the filesystem (EXT4) is not a recognized network FS (NFS/Lustre). If you want to force prefetching, start vLLM with --safetensors-load-strategy=prefetch. +(StageEngineCoreProc_stage0_replica0 pid=2302392) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 19413 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:39:02 [cpu_worker.py:255] Explicitly set (1.0/30.91) GiB for KV cache on node 0. +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:39:02 [kv_cache_utils.py:1869] GPU KV cache size: 7,168 tokens, Maximum concurrency for 2,048 tokens per request: 3.50x +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:39:02 [memory.py:91] Released 0 MiB after warm-up (anonymous RSS 20421 -> 20421 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:39:02 [core.py:354] init engine (profile, create kv cache, warmup model) took 0.19 s +(StageEngineCoreProc_stage0_replica0 pid=2302392) WARNING 09-23 17:39:02 [scheduler.py:182] Using custom scheduler class vllm_omni.core.sched.omni_ar_scheduler.OmniARAsyncScheduler. This scheduler interface is not public and compatibility may not be maintained. If you have subclassed Scheduler instead of AsyncScheduler, you will see degraded performance due to async scheduling being disabled. +(StageEngineCoreProc_stage0_replica0 pid=2302392) WARNING 09-23 17:39:02 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2302392) WARNING 09-23 17:39:02 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:39:02 [factory.py:46] Created connector: SharedMemoryConnector +(StageEngineCoreProc_stage0_replica0 pid=2302392) INFO 09-23 17:39:03 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +INFO 09-23 17:39:03 [stage_runtime.py:943] [StageRuntime] Stage 0 engine startup completed +INFO 09-23 17:39:03 [stage_engine_core_client.py:159] [StageEngineCoreClient] stage-0 [rep-0] initializing EngineCore +INFO 09-23 17:39:03 [stage_engine_core_client.py:215] [StageEngineCoreClient] stage-0 [rep-0] EngineCore running +INFO 09-23 17:39:03 [stage_runtime.py:958] [StageRuntime] Stage 0 initialized +INFO 09-23 17:39:03 [stage_runtime.py:853] [stage_init] Stage-1 set runtime devices: 0 +W0923 17:39:08.135000 2302497 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +W0923 17:39:08.162000 2302497 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +WARNING 09-23 17:39:09 [importing.py:65] Triton is installed, but doesn't include CPU backend. Disabling Triton. +INFO 09-23 17:39:09 [importing.py:88] Triton not installed or not compatible; certain GPU-related functions will not be available. +/home/zhout/project/edge_infer/vllm-omni-edge/vllm_omni/version.py:55: RuntimeWarning: vLLM and vLLM-Omni appear to have mismatched major/minor versions: + --> vLLM-Omni version 0.29.0rc2.dev71+g00510ce38.d20260922 + --> vLLM version 0.28.0 +This will likely cause compatibility issues. + warn_if_misaligned_vllm_version() +INFO 09-23 17:39:10 [patch.py:259] NVFP4 W4A4 weight_scale NaN-clamp: installed. +INFO 09-23 17:39:10 [patch.py:510] inductor factorable-divisibility patch: installed. +INFO 09-23 17:39:10 [patch.py:646] CPU AOT compile-cache load shim installed: compiled models are reused across engine starts instead of being recompiled. +INFO 09-23 17:39:10 [patch.py:756] CPU weight-load memory release installed (set VLLM_OMNI_CPU_RELEASE_MEMORY=0 to disable). +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:11 [core.py:122] Initializing a V1 LLM engine (v0.28.0) with config: model='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', speculative_config=None, tokenizer='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=512, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=None, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False, jit_monitor_mode='warn', jit_monitor_verbose=False), seed=0, served_model_name=/home/zhout/project/edge_infer/models/MiniCPM-o-4_5, enable_prefix_caching=False, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_vision_items_per_batch': 0, 'encoder_cudagraph_max_frames_per_batch': None, 'compile_sizes': None, 'compile_ranges_endpoints': [512], 'inductor_compile_config': {'enable_auto_functionalized_v2': False}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'enable_qk_norm_rope_fusion': False, 'fuse_rope_kvcache_cat_mla': False, 'fuse_act_padding': False, 'fuse_qk_norm_rope_kvcache': False}, 'max_cudagraph_capture_size': None, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']), enable_flashinfer_autotune=True, enable_cutedsl_warmup=True, enable_jit_warmup=True, enable_bf16x3_router_gemm=False, moe_backend='auto', linear_backend='auto') +[W923 17:39:12.211547924 utils.cpp:68] Warning: NUMA binding: Using MEMBIND policy for memory allocation on the NUMA nodes (0). Memory allocations will be strictly bound to these NUMA nodes. (function init_cpu_memory_env) +(StageEngineCoreProc_stage1_replica0 pid=2302497) WARNING 09-23 17:39:12 [vllm.py:652] Model Runner V2 requires Triton; using the V1 model runner instead. +(StageEngineCoreProc_stage1_replica0 pid=2302497) WARNING 09-23 17:39:12 [cpu_worker.py:127] libiomp is not found in LD_PRELOAD. For best performance, please follow the section `set LD_PRELOAD` in https://docs.vllm.ai/en/latest/getting_started/installation/cpu/ to setup required pre-loaded libraries. +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:12 [parallel_state.py:1638] world_size=1 rank=0 local_rank=0 distributed_init_method=file:///tmp/vllm_dist_61858aab472d470cb0cb86048a786e1b backend=gloo +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:12 [parallel_state.py:1982] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A, EPLB rank N/A +(StageEngineCoreProc_stage1_replica0 pid=2302497) WARNING 09-23 17:39:12 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2302497) [transformers] `MiniCPMOProcessor` defines `image_processor_class = 'AutoImageProcessor'`, which is deprecated. Register the correct mapping in `AutoImageProcessor` instead. +(StageEngineCoreProc_stage1_replica0 pid=2302497) [transformers] Requested torchvision backend is not available. Falling back to pil backend. +(StageEngineCoreProc_stage1_replica0 pid=2302497) [transformers] `MiniCPMOProcessor` defines `feature_extractor_class = 'WhisperFeatureExtractor'`, which is deprecated. Register the correct mapping in `AutoFeatureExtractor` instead. +(StageEngineCoreProc_stage1_replica0 pid=2302497) [transformers] Image processor MiniCPMVImageProcessor: kwargs ['max_slice_nums'] were applied for backward compatibility. To avoid this warning, add them to valid_kwargs: create a custom TypedDict extending ImagesKwargs with these keys and set it as the `valid_kwargs` class attribute. +(StageEngineCoreProc_stage1_replica0 pid=2302497) WARNING 09-23 17:39:20 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2302497) WARNING 09-23 17:39:20 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2302497) WARNING 09-23 17:39:20 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:20 [factory.py:46] Created connector: SharedMemoryConnector +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:20 [cpu_model_runner.py:131] Starting to load model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5... +(StageEngineCoreProc_stage1_replica0 pid=2302497) WARNING 09-23 17:39:20 [vllm.py:1285] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none +(StageEngineCoreProc_stage1_replica0 pid=2302497) WARNING 09-23 17:39:20 [vllm.py:1354] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:20 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:20 [compilation.py:329] Enabled custom fusions: norm_quant, act_quant +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:20 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:20 [selector.py:217] Using HND KV cache layout for CPU_ATTN backend. +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:20 [weight_utils.py:858] Filesystem type for checkpoints: EXT4. Checkpoint size: 17.46 GiB. Available RAM: 7.86 GiB. +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:20 [weight_utils.py:888] Auto-prefetch is disabled because the filesystem (EXT4) is not a recognized network FS (NFS/Lustre) and the checkpoint size (17.46 GiB) exceeds 90% of available RAM (7.86 GiB). +(StageEngineCoreProc_stage1_replica0 pid=2302497) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 1461 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:24 [cpu_worker.py:255] Explicitly set (1.0/30.91) GiB for KV cache on node 0. +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:24 [kv_cache_utils.py:1869] GPU KV cache size: 17,408 tokens, Maximum concurrency for 512 tokens per request: 34.00x +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:25 [memory.py:91] Released 0 MiB after warm-up (anonymous RSS 2484 -> 2484 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:25 [core.py:354] init engine (profile, create kv cache, warmup model) took 1.29 s +(StageEngineCoreProc_stage1_replica0 pid=2302497) WARNING 09-23 17:39:25 [scheduler.py:182] Using custom scheduler class vllm_omni.core.sched.omni_ar_scheduler.OmniARAsyncScheduler. This scheduler interface is not public and compatibility may not be maintained. If you have subclassed Scheduler instead of AsyncScheduler, you will see degraded performance due to async scheduling being disabled. +(StageEngineCoreProc_stage1_replica0 pid=2302497) WARNING 09-23 17:39:25 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2302497) WARNING 09-23 17:39:25 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:25 [factory.py:46] Created connector: SharedMemoryConnector +(StageEngineCoreProc_stage1_replica0 pid=2302497) INFO 09-23 17:39:26 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +INFO 09-23 17:39:26 [stage_runtime.py:943] [StageRuntime] Stage 1 engine startup completed +INFO 09-23 17:39:26 [stage_engine_core_client.py:159] [StageEngineCoreClient] stage-1 [rep-0] initializing EngineCore +INFO 09-23 17:39:26 [stage_engine_core_client.py:215] [StageEngineCoreClient] stage-1 [rep-0] EngineCore running +INFO 09-23 17:39:26 [stage_runtime.py:958] [StageRuntime] Stage 1 initialized +INFO 09-23 17:39:26 [stage_runtime.py:853] [stage_init] Stage-2 set runtime devices: 0 +W0923 17:39:32.405000 2302594 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +W0923 17:39:32.455000 2302594 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +WARNING 09-23 17:39:34 [importing.py:65] Triton is installed, but doesn't include CPU backend. Disabling Triton. +INFO 09-23 17:39:34 [importing.py:88] Triton not installed or not compatible; certain GPU-related functions will not be available. +/home/zhout/project/edge_infer/vllm-omni-edge/vllm_omni/version.py:55: RuntimeWarning: vLLM and vLLM-Omni appear to have mismatched major/minor versions: + --> vLLM-Omni version 0.29.0rc2.dev71+g00510ce38.d20260922 + --> vLLM version 0.28.0 +This will likely cause compatibility issues. + warn_if_misaligned_vllm_version() +INFO 09-23 17:39:35 [patch.py:259] NVFP4 W4A4 weight_scale NaN-clamp: installed. +INFO 09-23 17:39:35 [patch.py:510] inductor factorable-divisibility patch: installed. +INFO 09-23 17:39:35 [patch.py:646] CPU AOT compile-cache load shim installed: compiled models are reused across engine starts instead of being recompiled. +INFO 09-23 17:39:35 [patch.py:756] CPU weight-load memory release installed (set VLLM_OMNI_CPU_RELEASE_MEMORY=0 to disable). +(StageEngineCoreProc_stage2_replica0 pid=2302594) INFO 09-23 17:39:36 [core.py:122] Initializing a V1 LLM engine (v0.28.0) with config: model='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', speculative_config=None, tokenizer='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=4096, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=None, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False, jit_monitor_mode='warn', jit_monitor_verbose=False), seed=0, served_model_name=/home/zhout/project/edge_infer/models/MiniCPM-o-4_5, enable_prefix_caching=False, enable_chunked_prefill=False, pooler_config=None, compilation_config={'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_vision_items_per_batch': 0, 'encoder_cudagraph_max_frames_per_batch': None, 'compile_sizes': None, 'compile_ranges_endpoints': [4096], 'inductor_compile_config': {'enable_auto_functionalized_v2': False}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'enable_qk_norm_rope_fusion': False, 'fuse_rope_kvcache_cat_mla': False, 'fuse_act_padding': False, 'fuse_qk_norm_rope_kvcache': False}, 'max_cudagraph_capture_size': None, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']), enable_flashinfer_autotune=True, enable_cutedsl_warmup=True, enable_jit_warmup=True, enable_bf16x3_router_gemm=False, moe_backend='auto', linear_backend='auto') +[W923 17:39:36.885629043 utils.cpp:68] Warning: NUMA binding: Using MEMBIND policy for memory allocation on the NUMA nodes (0). Memory allocations will be strictly bound to these NUMA nodes. (function init_cpu_memory_env) +(StageEngineCoreProc_stage2_replica0 pid=2302594) WARNING 09-23 17:39:36 [vllm.py:652] Model Runner V2 requires Triton; using the V1 model runner instead. +(StageEngineCoreProc_stage2_replica0 pid=2302594) WARNING 09-23 17:39:36 [cpu_worker.py:127] libiomp is not found in LD_PRELOAD. For best performance, please follow the section `set LD_PRELOAD` in https://docs.vllm.ai/en/latest/getting_started/installation/cpu/ to setup required pre-loaded libraries. +(StageEngineCoreProc_stage2_replica0 pid=2302594) INFO 09-23 17:39:36 [parallel_state.py:1638] world_size=1 rank=0 local_rank=0 distributed_init_method=file:///tmp/vllm_dist_ff43f47fca5a47759bce928b8ce6d28e backend=gloo +(StageEngineCoreProc_stage2_replica0 pid=2302594) INFO 09-23 17:39:36 [parallel_state.py:1982] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A, EPLB rank N/A +(StageEngineCoreProc_stage2_replica0 pid=2302594) INFO 09-23 17:39:36 [factory.py:46] Created connector: SharedMemoryConnector +(StageEngineCoreProc_stage2_replica0 pid=2302594) INFO 09-23 17:39:36 [cpu_model_runner.py:131] Starting to load model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5... +(StageEngineCoreProc_stage2_replica0 pid=2302594) INFO 09-23 17:39:36 [weight_utils.py:858] Filesystem type for checkpoints: EXT4. Checkpoint size: 17.46 GiB. Available RAM: 5.93 GiB. +(StageEngineCoreProc_stage2_replica0 pid=2302594) INFO 09-23 17:39:36 [weight_utils.py:888] Auto-prefetch is disabled because the filesystem (EXT4) is not a recognized network FS (NFS/Lustre) and the checkpoint size (17.46 GiB) exceeds 90% of available RAM (5.93 GiB). +(StageEngineCoreProc_stage2_replica0 pid=2302594) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 3964 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage2_replica0 pid=2302594) INFO 09-23 17:39:46 [memory.py:91] Released 0 MiB after warm-up (anonymous RSS 3964 -> 3964 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage2_replica0 pid=2302594) INFO 09-23 17:39:46 [core.py:354] init engine (profile, create kv cache, warmup model) took 0.00 s +(StageEngineCoreProc_stage2_replica0 pid=2302594) WARNING 09-23 17:39:46 [scheduler.py:182] Using custom scheduler class vllm_omni.core.sched.omni_generation_scheduler.OmniGenerationScheduler. This scheduler interface is not public and compatibility may not be maintained. If you have subclassed Scheduler instead of AsyncScheduler, you will see degraded performance due to async scheduling being disabled. +(StageEngineCoreProc_stage2_replica0 pid=2302594) INFO 09-23 17:39:46 [factory.py:46] Created connector: SharedMemoryConnector +(StageEngineCoreProc_stage2_replica0 pid=2302594) WARNING 09-23 17:39:47 [vllm.py:1285] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none +(StageEngineCoreProc_stage2_replica0 pid=2302594) WARNING 09-23 17:39:47 [vllm.py:1354] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. +(StageEngineCoreProc_stage2_replica0 pid=2302594) INFO 09-23 17:39:47 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage2_replica0 pid=2302594) INFO 09-23 17:39:47 [compilation.py:329] Enabled custom fusions: norm_quant, act_quant +INFO 09-23 17:39:47 [stage_runtime.py:943] [StageRuntime] Stage 2 engine startup completed +INFO 09-23 17:39:47 [stage_engine_core_client.py:159] [StageEngineCoreClient] stage-2 [rep-0] initializing EngineCore +INFO 09-23 17:39:47 [stage_engine_core_client.py:215] [StageEngineCoreClient] stage-2 [rep-0] EngineCore running +INFO 09-23 17:39:47 [stage_runtime.py:958] [StageRuntime] Stage 2 initialized +[transformers] `MiniCPMOProcessor` defines `image_processor_class = 'AutoImageProcessor'`, which is deprecated. Register the correct mapping in `AutoImageProcessor` instead. +[transformers] Requested torchvision backend is not available. Falling back to pil backend. +[transformers] `MiniCPMOProcessor` defines `feature_extractor_class = 'WhisperFeatureExtractor'`, which is deprecated. Register the correct mapping in `AutoFeatureExtractor` instead. +INFO 09-23 17:40:10 [orchestrator.py:604] [Orchestrator] Starting event loop +INFO 09-23 17:40:10 [async_omni_engine.py:323] [AsyncOmniEngine] Orchestrator ready with 3 stages +INFO 09-23 17:40:10 [omni_base.py:235] [Omni] AsyncOmniEngine initialized in 101.22 seconds +INFO 09-23 17:40:10 [omni_base.py:255] [Omni] Initialized with 3 stages for model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5 +WARNING 09-23 17:40:10 [input_processor.py:296] Passing raw prompts to InputProcessor is deprecated and will be removed in v0.18. 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There are no other visible elements, text, or details. +vllm_token_ids: +[785, 2168, 4933, 264, 6437, 2518, 9334, 30188, 389, 264, 4158, 4004, 13, 2619, 525, 902, 1008, 9434, 5424, 11, 1467, 11, 476, 3565, 13, 151704, 151645] diff --git a/benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_image/minicpmo_cpu_image.log b/benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_image/minicpmo_cpu_image.log new file mode 100644 index 000000000..e429a838a --- /dev/null +++ b/benchmarks/edge_harness/results/e2e_expansion_20260923/evidence/minicpmo_wsl_cpu_image/minicpmo_cpu_image.log @@ -0,0 +1,248 @@ +W0923 17:34:57.241000 2301854 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +W0923 17:34:57.265000 2301854 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +WARNING 09-23 17:34:58 [importing.py:65] Triton is installed, but doesn't include CPU backend. Disabling Triton. +INFO 09-23 17:34:58 [importing.py:88] Triton not installed or not compatible; certain GPU-related functions will not be available. +/home/zhout/project/edge_infer/vllm-omni-edge/vllm_omni/version.py:55: RuntimeWarning: vLLM and vLLM-Omni appear to have mismatched major/minor versions: + --> vLLM-Omni version 0.29.0rc2.dev71+g00510ce38.d20260922 + --> vLLM version 0.28.0 +This will likely cause compatibility issues. + warn_if_misaligned_vllm_version() +INFO 09-23 17:34:59 [patch.py:259] NVFP4 W4A4 weight_scale NaN-clamp: installed. +INFO 09-23 17:34:59 [patch.py:510] inductor factorable-divisibility patch: installed. +INFO 09-23 17:34:59 [patch.py:646] CPU AOT compile-cache load shim installed: compiled models are reused across engine starts instead of being recompiled. +INFO 09-23 17:34:59 [patch.py:756] CPU weight-load memory release installed (set VLLM_OMNI_CPU_RELEASE_MEMORY=0 to disable). +==================== + vllm version: 0.28.0 + ==================== +INFO 09-23 17:34:59 [omni_base.py:216] [Omni] Initializing with model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5 +INFO 09-23 17:34:59 [async_omni_engine.py:172] [AsyncOmniEngine] Initializing with model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5 +INFO 09-23 17:34:59 [async_omni_engine.py:290] [AsyncOmniEngine] Launching Orchestrator thread with 3 stages +INFO 09-23 17:35:00 [stage_init_utils.py:768] [stage_init] Set VLLM_WORKER_MULTIPROC_METHOD=spawn +INFO 09-23 17:35:00 [initialization.py:356] Loaded OmniTransferConfig with 1 connector configurations +WARNING 09-23 17:35:00 [utils.py:501] Dropping unknown OmniEngineArgs field 'inline_diffusion' (not declared on the dataclass) +WARNING 09-23 17:35:00 [utils.py:501] Dropping unknown OmniEngineArgs field 'shm_threshold_bytes' (not declared on the dataclass) +WARNING 09-23 17:35:00 [arg_utils.py:1719] The global random seed is set to 0. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. +INFO 09-23 17:35:08 [model.py:672] Resolved architecture: MiniCPMO45OmniForConditionalGeneration +INFO 09-23 17:35:08 [model.py:1965] Using max model len 2048 +WARNING 09-23 17:35:08 [model.py:963] Model does not support mm_device_do_normalize, forcing mm_device_do_normalize = False. +INFO 09-23 17:35:09 [scheduler.py:242] Chunked prefill is enabled with max_num_batched_tokens=2048. +WARNING 09-23 17:35:09 [vllm.py:1285] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none +WARNING 09-23 17:35:09 [vllm.py:1354] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. +INFO 09-23 17:35:09 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +WARNING 09-23 17:35:09 [vllm.py:652] Model Runner V2 requires Triton; using the V1 model runner instead. +INFO 09-23 17:35:09 [compilation.py:329] Enabled custom fusions: norm_quant, act_quant +WARNING 09-23 17:35:09 [utils.py:501] Dropping unknown OmniEngineArgs field 'inline_diffusion' (not declared on the dataclass) +WARNING 09-23 17:35:09 [utils.py:501] Dropping unknown OmniEngineArgs field 'shm_threshold_bytes' (not declared on the dataclass) +WARNING 09-23 17:35:09 [arg_utils.py:1719] The global random seed is set to 0. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. +INFO 09-23 17:35:09 [model.py:672] Resolved architecture: MiniCPMO45OmniForConditionalGeneration +INFO 09-23 17:35:09 [model.py:1965] Using max model len 512 +WARNING 09-23 17:35:09 [model.py:963] Model does not support mm_device_do_normalize, forcing mm_device_do_normalize = False. +INFO 09-23 17:35:09 [model.py:1965] Using max model len 512 +INFO 09-23 17:35:09 [scheduler.py:242] Chunked prefill is enabled with max_num_batched_tokens=512. +INFO 09-23 17:35:09 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +WARNING 09-23 17:35:09 [utils.py:501] Dropping unknown OmniEngineArgs field 'inline_diffusion' (not declared on the dataclass) +WARNING 09-23 17:35:09 [utils.py:501] Dropping unknown OmniEngineArgs field 'shm_threshold_bytes' (not declared on the dataclass) +WARNING 09-23 17:35:09 [arg_utils.py:1719] The global random seed is set to 0. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. +INFO 09-23 17:35:17 [model.py:672] Resolved architecture: MiniCPMO45Code2Wav +INFO 09-23 17:35:17 [model.py:1965] Using max model len 4096 +WARNING 09-23 17:35:17 [arg_utils.py:2664] This model does not officially support disabling chunked prefill. Disabling this manually may cause the engine to crash or produce incorrect outputs. +INFO 09-23 17:35:17 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +INFO 09-23 17:35:17 [stage_runtime.py:853] [stage_init] Stage-0 set runtime devices: 0 +W0923 17:35:21.189000 2301932 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +W0923 17:35:21.214000 2301932 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +WARNING 09-23 17:35:22 [importing.py:65] Triton is installed, but doesn't include CPU backend. Disabling Triton. +INFO 09-23 17:35:22 [importing.py:88] Triton not installed or not compatible; certain GPU-related functions will not be available. +/home/zhout/project/edge_infer/vllm-omni-edge/vllm_omni/version.py:55: RuntimeWarning: vLLM and vLLM-Omni appear to have mismatched major/minor versions: + --> vLLM-Omni version 0.29.0rc2.dev71+g00510ce38.d20260922 + --> vLLM version 0.28.0 +This will likely cause compatibility issues. + warn_if_misaligned_vllm_version() +INFO 09-23 17:35:23 [patch.py:259] NVFP4 W4A4 weight_scale NaN-clamp: installed. +INFO 09-23 17:35:23 [patch.py:510] inductor factorable-divisibility patch: installed. +INFO 09-23 17:35:23 [patch.py:646] CPU AOT compile-cache load shim installed: compiled models are reused across engine starts instead of being recompiled. +INFO 09-23 17:35:23 [patch.py:756] CPU weight-load memory release installed (set VLLM_OMNI_CPU_RELEASE_MEMORY=0 to disable). +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:23 [core.py:122] Initializing a V1 LLM engine (v0.28.0) with config: model='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', speculative_config=None, tokenizer='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=2048, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=None, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False, jit_monitor_mode='warn', jit_monitor_verbose=False), seed=0, served_model_name=/home/zhout/project/edge_infer/models/MiniCPM-o-4_5, enable_prefix_caching=False, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_vision_items_per_batch': 0, 'encoder_cudagraph_max_frames_per_batch': None, 'compile_sizes': None, 'compile_ranges_endpoints': [2048], 'inductor_compile_config': {'enable_auto_functionalized_v2': False}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'enable_qk_norm_rope_fusion': False, 'fuse_rope_kvcache_cat_mla': False, 'fuse_act_padding': False, 'fuse_qk_norm_rope_kvcache': False}, 'max_cudagraph_capture_size': None, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']), enable_flashinfer_autotune=True, enable_cutedsl_warmup=True, enable_jit_warmup=True, enable_bf16x3_router_gemm=False, moe_backend='auto', linear_backend='auto') +[W923 17:35:24.784797782 utils.cpp:68] Warning: NUMA binding: Using MEMBIND policy for memory allocation on the NUMA nodes (0). Memory allocations will be strictly bound to these NUMA nodes. (function init_cpu_memory_env) +(StageEngineCoreProc_stage0_replica0 pid=2301932) WARNING 09-23 17:35:24 [vllm.py:652] Model Runner V2 requires Triton; using the V1 model runner instead. +(StageEngineCoreProc_stage0_replica0 pid=2301932) WARNING 09-23 17:35:24 [cpu_worker.py:127] libiomp is not found in LD_PRELOAD. For best performance, please follow the section `set LD_PRELOAD` in https://docs.vllm.ai/en/latest/getting_started/installation/cpu/ to setup required pre-loaded libraries. +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:24 [parallel_state.py:1638] world_size=1 rank=0 local_rank=0 distributed_init_method=file:///tmp/vllm_dist_2d48085d7a9347c8b8326460f316585f backend=gloo +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:24 [parallel_state.py:1982] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A, EPLB rank N/A +(StageEngineCoreProc_stage0_replica0 pid=2301932) WARNING 09-23 17:35:24 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2301932) [transformers] `MiniCPMOProcessor` defines `image_processor_class = 'AutoImageProcessor'`, which is deprecated. Register the correct mapping in `AutoImageProcessor` instead. +(StageEngineCoreProc_stage0_replica0 pid=2301932) [transformers] Requested torchvision backend is not available. Falling back to pil backend. +(StageEngineCoreProc_stage0_replica0 pid=2301932) [transformers] `MiniCPMOProcessor` defines `feature_extractor_class = 'WhisperFeatureExtractor'`, which is deprecated. Register the correct mapping in `AutoFeatureExtractor` instead. +(StageEngineCoreProc_stage0_replica0 pid=2301932) WARNING 09-23 17:35:27 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2301932) WARNING 09-23 17:35:27 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2301932) WARNING 09-23 17:35:27 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:27 [cpu_model_runner.py:131] Starting to load model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5... +(StageEngineCoreProc_stage0_replica0 pid=2301932) WARNING 09-23 17:35:27 [vllm.py:1285] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none +(StageEngineCoreProc_stage0_replica0 pid=2301932) WARNING 09-23 17:35:27 [vllm.py:1354] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:27 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:27 [compilation.py:329] Enabled custom fusions: norm_quant, act_quant +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:31 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:31 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:31 [selector.py:217] Using HND KV cache layout for CPU_ATTN backend. +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:35 [weight_utils.py:858] Filesystem type for checkpoints: EXT4. Checkpoint size: 17.46 GiB. Available RAM: 25.93 GiB. +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:35 [weight_utils.py:881] Auto-prefetch is disabled because the filesystem (EXT4) is not a recognized network FS (NFS/Lustre). If you want to force prefetching, start vLLM with --safetensors-load-strategy=prefetch. +(StageEngineCoreProc_stage0_replica0 pid=2301932) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 20462 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:46 [cpu_worker.py:255] Explicitly set (1.0/30.91) GiB for KV cache on node 0. +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:46 [kv_cache_utils.py:1869] GPU KV cache size: 7,168 tokens, Maximum concurrency for 2,048 tokens per request: 3.50x +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:47 [memory.py:91] Released -0 MiB after warm-up (anonymous RSS 21470 -> 21470 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:47 [core.py:354] init engine (profile, create kv cache, warmup model) took 0.37 s +(StageEngineCoreProc_stage0_replica0 pid=2301932) WARNING 09-23 17:35:47 [scheduler.py:182] Using custom scheduler class vllm_omni.core.sched.omni_ar_scheduler.OmniARAsyncScheduler. This scheduler interface is not public and compatibility may not be maintained. If you have subclassed Scheduler instead of AsyncScheduler, you will see degraded performance due to async scheduling being disabled. +(StageEngineCoreProc_stage0_replica0 pid=2301932) WARNING 09-23 17:35:47 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2301932) WARNING 09-23 17:35:47 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:47 [factory.py:46] Created connector: SharedMemoryConnector +(StageEngineCoreProc_stage0_replica0 pid=2301932) INFO 09-23 17:35:47 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +INFO 09-23 17:35:47 [stage_runtime.py:943] [StageRuntime] Stage 0 engine startup completed +INFO 09-23 17:35:47 [stage_engine_core_client.py:159] [StageEngineCoreClient] stage-0 [rep-0] initializing EngineCore +INFO 09-23 17:35:48 [stage_engine_core_client.py:215] [StageEngineCoreClient] stage-0 [rep-0] EngineCore running +INFO 09-23 17:35:48 [stage_runtime.py:958] [StageRuntime] Stage 0 initialized +INFO 09-23 17:35:48 [stage_runtime.py:853] [stage_init] Stage-1 set runtime devices: 0 +W0923 17:35:53.309000 2302038 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +W0923 17:35:53.340000 2302038 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +WARNING 09-23 17:35:54 [importing.py:65] Triton is installed, but doesn't include CPU backend. Disabling Triton. +INFO 09-23 17:35:54 [importing.py:88] Triton not installed or not compatible; certain GPU-related functions will not be available. +/home/zhout/project/edge_infer/vllm-omni-edge/vllm_omni/version.py:55: RuntimeWarning: vLLM and vLLM-Omni appear to have mismatched major/minor versions: + --> vLLM-Omni version 0.29.0rc2.dev71+g00510ce38.d20260922 + --> vLLM version 0.28.0 +This will likely cause compatibility issues. + warn_if_misaligned_vllm_version() +INFO 09-23 17:35:56 [patch.py:259] NVFP4 W4A4 weight_scale NaN-clamp: installed. +INFO 09-23 17:35:56 [patch.py:510] inductor factorable-divisibility patch: installed. +INFO 09-23 17:35:56 [patch.py:646] CPU AOT compile-cache load shim installed: compiled models are reused across engine starts instead of being recompiled. +INFO 09-23 17:35:56 [patch.py:756] CPU weight-load memory release installed (set VLLM_OMNI_CPU_RELEASE_MEMORY=0 to disable). +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:35:56 [core.py:122] Initializing a V1 LLM engine (v0.28.0) with config: model='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', speculative_config=None, tokenizer='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=512, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=None, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False, jit_monitor_mode='warn', jit_monitor_verbose=False), seed=0, served_model_name=/home/zhout/project/edge_infer/models/MiniCPM-o-4_5, enable_prefix_caching=False, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_vision_items_per_batch': 0, 'encoder_cudagraph_max_frames_per_batch': None, 'compile_sizes': None, 'compile_ranges_endpoints': [512], 'inductor_compile_config': {'enable_auto_functionalized_v2': False}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'enable_qk_norm_rope_fusion': False, 'fuse_rope_kvcache_cat_mla': False, 'fuse_act_padding': False, 'fuse_qk_norm_rope_kvcache': False}, 'max_cudagraph_capture_size': None, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']), enable_flashinfer_autotune=True, enable_cutedsl_warmup=True, enable_jit_warmup=True, enable_bf16x3_router_gemm=False, moe_backend='auto', linear_backend='auto') +[W923 17:35:57.014267214 utils.cpp:68] Warning: NUMA binding: Using MEMBIND policy for memory allocation on the NUMA nodes (0). Memory allocations will be strictly bound to these NUMA nodes. (function init_cpu_memory_env) +(StageEngineCoreProc_stage1_replica0 pid=2302038) WARNING 09-23 17:35:57 [vllm.py:652] Model Runner V2 requires Triton; using the V1 model runner instead. +(StageEngineCoreProc_stage1_replica0 pid=2302038) WARNING 09-23 17:35:57 [cpu_worker.py:127] libiomp is not found in LD_PRELOAD. For best performance, please follow the section `set LD_PRELOAD` in https://docs.vllm.ai/en/latest/getting_started/installation/cpu/ to setup required pre-loaded libraries. +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:35:57 [parallel_state.py:1638] world_size=1 rank=0 local_rank=0 distributed_init_method=file:///tmp/vllm_dist_a193d171d2d94114aacfb5dcecee4ed5 backend=gloo +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:35:57 [parallel_state.py:1982] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A, EPLB rank N/A +(StageEngineCoreProc_stage1_replica0 pid=2302038) WARNING 09-23 17:35:57 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2302038) [transformers] `MiniCPMOProcessor` defines `image_processor_class = 'AutoImageProcessor'`, which is deprecated. Register the correct mapping in `AutoImageProcessor` instead. +(StageEngineCoreProc_stage1_replica0 pid=2302038) [transformers] Requested torchvision backend is not available. Falling back to pil backend. +(StageEngineCoreProc_stage1_replica0 pid=2302038) [transformers] `MiniCPMOProcessor` defines `feature_extractor_class = 'WhisperFeatureExtractor'`, which is deprecated. Register the correct mapping in `AutoFeatureExtractor` instead. +(StageEngineCoreProc_stage1_replica0 pid=2302038) [transformers] Image processor MiniCPMVImageProcessor: kwargs ['max_slice_nums'] were applied for backward compatibility. To avoid this warning, add them to valid_kwargs: create a custom TypedDict extending ImagesKwargs with these keys and set it as the `valid_kwargs` class attribute. +(StageEngineCoreProc_stage1_replica0 pid=2302038) WARNING 09-23 17:36:06 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2302038) WARNING 09-23 17:36:06 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2302038) WARNING 09-23 17:36:06 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:36:06 [factory.py:46] Created connector: SharedMemoryConnector +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:36:06 [cpu_model_runner.py:131] Starting to load model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5... +(StageEngineCoreProc_stage1_replica0 pid=2302038) WARNING 09-23 17:36:06 [vllm.py:1285] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none +(StageEngineCoreProc_stage1_replica0 pid=2302038) WARNING 09-23 17:36:06 [vllm.py:1354] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:36:06 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:36:06 [compilation.py:329] Enabled custom fusions: norm_quant, act_quant +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:36:06 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:36:06 [selector.py:217] Using HND KV cache layout for CPU_ATTN backend. +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:36:07 [weight_utils.py:858] Filesystem type for checkpoints: EXT4. Checkpoint size: 17.46 GiB. Available RAM: 6.75 GiB. +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:36:07 [weight_utils.py:888] Auto-prefetch is disabled because the filesystem (EXT4) is not a recognized network FS (NFS/Lustre) and the checkpoint size (17.46 GiB) exceeds 90% of available RAM (6.75 GiB). +(StageEngineCoreProc_stage1_replica0 pid=2302038) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 1462 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:36:09 [cpu_worker.py:255] Explicitly set (1.0/30.91) GiB for KV cache on node 0. +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:36:09 [kv_cache_utils.py:1869] GPU KV cache size: 17,408 tokens, Maximum concurrency for 512 tokens per request: 34.00x +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:36:10 [memory.py:91] Released 0 MiB after warm-up (anonymous RSS 2484 -> 2484 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:36:10 [core.py:354] init engine (profile, create kv cache, warmup model) took 0.89 s +(StageEngineCoreProc_stage1_replica0 pid=2302038) WARNING 09-23 17:36:10 [scheduler.py:182] Using custom scheduler class vllm_omni.core.sched.omni_ar_scheduler.OmniARAsyncScheduler. This scheduler interface is not public and compatibility may not be maintained. If you have subclassed Scheduler instead of AsyncScheduler, you will see degraded performance due to async scheduling being disabled. +(StageEngineCoreProc_stage1_replica0 pid=2302038) WARNING 09-23 17:36:10 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2302038) WARNING 09-23 17:36:10 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:36:10 [factory.py:46] Created connector: SharedMemoryConnector +(StageEngineCoreProc_stage1_replica0 pid=2302038) INFO 09-23 17:36:11 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +INFO 09-23 17:36:11 [stage_runtime.py:943] [StageRuntime] Stage 1 engine startup completed +INFO 09-23 17:36:11 [stage_engine_core_client.py:159] [StageEngineCoreClient] stage-1 [rep-0] initializing EngineCore +INFO 09-23 17:36:11 [stage_engine_core_client.py:215] [StageEngineCoreClient] stage-1 [rep-0] EngineCore running +INFO 09-23 17:36:11 [stage_runtime.py:958] [StageRuntime] Stage 1 initialized +INFO 09-23 17:36:11 [stage_runtime.py:853] [stage_init] Stage-2 set runtime devices: 0 +W0923 17:36:16.105000 2302144 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +W0923 17:36:16.133000 2302144 torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +WARNING 09-23 17:36:17 [importing.py:65] Triton is installed, but doesn't include CPU backend. Disabling Triton. +INFO 09-23 17:36:17 [importing.py:88] Triton not installed or not compatible; certain GPU-related functions will not be available. +/home/zhout/project/edge_infer/vllm-omni-edge/vllm_omni/version.py:55: RuntimeWarning: vLLM and vLLM-Omni appear to have mismatched major/minor versions: + --> vLLM-Omni version 0.29.0rc2.dev71+g00510ce38.d20260922 + --> vLLM version 0.28.0 +This will likely cause compatibility issues. + warn_if_misaligned_vllm_version() +INFO 09-23 17:36:18 [patch.py:259] NVFP4 W4A4 weight_scale NaN-clamp: installed. +INFO 09-23 17:36:18 [patch.py:510] inductor factorable-divisibility patch: installed. +INFO 09-23 17:36:18 [patch.py:646] CPU AOT compile-cache load shim installed: compiled models are reused across engine starts instead of being recompiled. +INFO 09-23 17:36:19 [patch.py:756] CPU weight-load memory release installed (set VLLM_OMNI_CPU_RELEASE_MEMORY=0 to disable). +(StageEngineCoreProc_stage2_replica0 pid=2302144) INFO 09-23 17:36:19 [core.py:122] Initializing a V1 LLM engine (v0.28.0) with config: model='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', speculative_config=None, tokenizer='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=4096, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=None, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False, jit_monitor_mode='warn', jit_monitor_verbose=False), seed=0, served_model_name=/home/zhout/project/edge_infer/models/MiniCPM-o-4_5, enable_prefix_caching=False, enable_chunked_prefill=False, pooler_config=None, compilation_config={'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_vision_items_per_batch': 0, 'encoder_cudagraph_max_frames_per_batch': None, 'compile_sizes': None, 'compile_ranges_endpoints': [4096], 'inductor_compile_config': {'enable_auto_functionalized_v2': False}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'enable_qk_norm_rope_fusion': False, 'fuse_rope_kvcache_cat_mla': False, 'fuse_act_padding': False, 'fuse_qk_norm_rope_kvcache': False}, 'max_cudagraph_capture_size': None, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']), enable_flashinfer_autotune=True, enable_cutedsl_warmup=True, enable_jit_warmup=True, enable_bf16x3_router_gemm=False, moe_backend='auto', linear_backend='auto') +[W923 17:36:19.181532864 utils.cpp:68] Warning: NUMA binding: Using MEMBIND policy for memory allocation on the NUMA nodes (0). Memory allocations will be strictly bound to these NUMA nodes. (function init_cpu_memory_env) +(StageEngineCoreProc_stage2_replica0 pid=2302144) WARNING 09-23 17:36:19 [vllm.py:652] Model Runner V2 requires Triton; using the V1 model runner instead. +(StageEngineCoreProc_stage2_replica0 pid=2302144) WARNING 09-23 17:36:19 [cpu_worker.py:127] libiomp is not found in LD_PRELOAD. For best performance, please follow the section `set LD_PRELOAD` in https://docs.vllm.ai/en/latest/getting_started/installation/cpu/ to setup required pre-loaded libraries. +(StageEngineCoreProc_stage2_replica0 pid=2302144) INFO 09-23 17:36:19 [parallel_state.py:1638] world_size=1 rank=0 local_rank=0 distributed_init_method=file:///tmp/vllm_dist_eac150642a1c4fc4a4d408f0589eaeda backend=gloo +(StageEngineCoreProc_stage2_replica0 pid=2302144) INFO 09-23 17:36:20 [parallel_state.py:1982] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A, EPLB rank N/A +(StageEngineCoreProc_stage2_replica0 pid=2302144) INFO 09-23 17:36:20 [factory.py:46] Created connector: SharedMemoryConnector +(StageEngineCoreProc_stage2_replica0 pid=2302144) INFO 09-23 17:36:20 [cpu_model_runner.py:131] Starting to load model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5... +(StageEngineCoreProc_stage2_replica0 pid=2302144) INFO 09-23 17:36:20 [weight_utils.py:858] Filesystem type for checkpoints: EXT4. Checkpoint size: 17.46 GiB. Available RAM: 5.85 GiB. +(StageEngineCoreProc_stage2_replica0 pid=2302144) INFO 09-23 17:36:20 [weight_utils.py:888] Auto-prefetch is disabled because the filesystem (EXT4) is not a recognized network FS (NFS/Lustre) and the checkpoint size (17.46 GiB) exceeds 90% of available RAM (5.85 GiB). +(StageEngineCoreProc_stage2_replica0 pid=2302144) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 3964 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage2_replica0 pid=2302144) INFO 09-23 17:36:29 [memory.py:91] Released -0 MiB after warm-up (anonymous RSS 3964 -> 3964 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage2_replica0 pid=2302144) INFO 09-23 17:36:29 [core.py:354] init engine (profile, create kv cache, warmup model) took 0.01 s +(StageEngineCoreProc_stage2_replica0 pid=2302144) WARNING 09-23 17:36:30 [scheduler.py:182] Using custom scheduler class vllm_omni.core.sched.omni_generation_scheduler.OmniGenerationScheduler. This scheduler interface is not public and compatibility may not be maintained. If you have subclassed Scheduler instead of AsyncScheduler, you will see degraded performance due to async scheduling being disabled. +(StageEngineCoreProc_stage2_replica0 pid=2302144) INFO 09-23 17:36:30 [factory.py:46] Created connector: SharedMemoryConnector +(StageEngineCoreProc_stage2_replica0 pid=2302144) WARNING 09-23 17:36:30 [vllm.py:1285] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none +(StageEngineCoreProc_stage2_replica0 pid=2302144) WARNING 09-23 17:36:30 [vllm.py:1354] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. +(StageEngineCoreProc_stage2_replica0 pid=2302144) INFO 09-23 17:36:30 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage2_replica0 pid=2302144) INFO 09-23 17:36:30 [compilation.py:329] Enabled custom fusions: norm_quant, act_quant +INFO 09-23 17:36:30 [stage_runtime.py:943] [StageRuntime] Stage 2 engine startup completed +INFO 09-23 17:36:30 [stage_engine_core_client.py:159] [StageEngineCoreClient] stage-2 [rep-0] initializing EngineCore +INFO 09-23 17:36:30 [stage_engine_core_client.py:215] [StageEngineCoreClient] stage-2 [rep-0] EngineCore running +INFO 09-23 17:36:30 [stage_runtime.py:958] [StageRuntime] Stage 2 initialized +[transformers] `MiniCPMOProcessor` defines `image_processor_class = 'AutoImageProcessor'`, which is deprecated. Register the correct mapping in `AutoImageProcessor` instead. +[transformers] Requested torchvision backend is not available. Falling back to pil backend. +[transformers] `MiniCPMOProcessor` defines `feature_extractor_class = 'WhisperFeatureExtractor'`, which is deprecated. Register the correct mapping in `AutoFeatureExtractor` instead. +INFO 09-23 17:36:52 [orchestrator.py:604] [Orchestrator] Starting event loop +INFO 09-23 17:36:52 [async_omni_engine.py:323] [AsyncOmniEngine] Orchestrator ready with 3 stages +INFO 09-23 17:36:52 [omni_base.py:235] [Omni] AsyncOmniEngine initialized in 112.44 seconds +INFO 09-23 17:36:52 [omni_base.py:255] [Omni] Initialized with 3 stages for model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5 +WARNING 09-23 17:36:52 [input_processor.py:296] Passing raw prompts to InputProcessor is deprecated and will be removed in v0.18. You should instead pass the outputs of Renderer.render_cmpl() or Renderer.render_chat(). + Processed prompts: 0%| | 0/1 [00:00 is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +W0923 17:31:25.660000 2301160 .venvs/omni-cpu/lib/python3.12/site-packages/torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +WARNING 09-23 17:31:27 [importing.py:65] Triton is installed, but doesn't include CPU backend. Disabling Triton. +INFO 09-23 17:31:27 [importing.py:88] Triton not installed or not compatible; certain GPU-related functions will not be available. +INFO 09-23 17:31:29 [patch.py:252] NVFP4 W4A4 weight_scale NaN-clamp: installed. +INFO 09-23 17:31:29 [patch.py:503] inductor factorable-divisibility patch: installed. +INFO 09-23 17:31:29 [patch.py:633] CPU AOT compile-cache load shim installed: compiled models are reused across engine starts instead of being recompiled. +INFO 09-23 17:31:29 [patch.py:743] CPU weight-load memory release installed (set VLLM_OMNI_CPU_RELEASE_MEMORY=0 to disable). +==================== + vllm version: 0.28.0 + ==================== +INFO 09-23 17:31:29 [omni_base.py:216] [Omni] Initializing with model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5 +INFO 09-23 17:31:29 [async_omni_engine.py:161] [AsyncOmniEngine] Initializing with model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5 +INFO 09-23 17:31:29 [async_omni_engine.py:286] [AsyncOmniEngine] Launching Orchestrator thread with 3 stages +INFO 09-23 17:31:29 [stage_init_utils.py:765] [stage_init] Set VLLM_WORKER_MULTIPROC_METHOD=spawn +INFO 09-23 17:31:29 [initialization.py:356] Loaded OmniTransferConfig with 1 connector configurations +WARNING 09-23 17:31:29 [utils.py:893] Dropping unknown OmniEngineArgs field 'inline_diffusion' (not declared on the dataclass) +WARNING 09-23 17:31:29 [utils.py:893] Dropping unknown OmniEngineArgs field 'shm_threshold_bytes' (not declared on the dataclass) +WARNING 09-23 17:31:30 [arg_utils.py:1719] The global random seed is set to 0. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. +INFO 09-23 17:31:39 [model.py:672] Resolved architecture: MiniCPMO45OmniForConditionalGeneration +INFO 09-23 17:31:39 [model.py:1965] Using max model len 2048 +WARNING 09-23 17:31:39 [model.py:963] Model does not support mm_device_do_normalize, forcing mm_device_do_normalize = False. +INFO 09-23 17:31:39 [scheduler.py:242] Chunked prefill is enabled with max_num_batched_tokens=2048. +WARNING 09-23 17:31:39 [vllm.py:1285] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none +WARNING 09-23 17:31:39 [vllm.py:1354] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. +INFO 09-23 17:31:39 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +WARNING 09-23 17:31:39 [vllm.py:652] Model Runner V2 requires Triton; using the V1 model runner instead. +INFO 09-23 17:31:39 [compilation.py:329] Enabled custom fusions: norm_quant, act_quant +WARNING 09-23 17:31:39 [utils.py:893] Dropping unknown OmniEngineArgs field 'inline_diffusion' (not declared on the dataclass) +WARNING 09-23 17:31:39 [utils.py:893] Dropping unknown OmniEngineArgs field 'shm_threshold_bytes' (not declared on the dataclass) +WARNING 09-23 17:31:39 [arg_utils.py:1719] The global random seed is set to 0. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. +INFO 09-23 17:31:39 [model.py:672] Resolved architecture: MiniCPMO45OmniForConditionalGeneration +INFO 09-23 17:31:39 [model.py:1965] Using max model len 512 +WARNING 09-23 17:31:39 [model.py:963] Model does not support mm_device_do_normalize, forcing mm_device_do_normalize = False. +INFO 09-23 17:31:39 [model.py:1965] Using max model len 512 +INFO 09-23 17:31:39 [scheduler.py:242] Chunked prefill is enabled with max_num_batched_tokens=512. +INFO 09-23 17:31:39 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +WARNING 09-23 17:31:39 [utils.py:893] Dropping unknown OmniEngineArgs field 'inline_diffusion' (not declared on the dataclass) +WARNING 09-23 17:31:39 [utils.py:893] Dropping unknown OmniEngineArgs field 'shm_threshold_bytes' (not declared on the dataclass) +WARNING 09-23 17:31:39 [arg_utils.py:1719] The global random seed is set to 0. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. +INFO 09-23 17:31:48 [model.py:672] Resolved architecture: MiniCPMO45Code2Wav +INFO 09-23 17:31:48 [model.py:1965] Using max model len 4096 +WARNING 09-23 17:31:48 [arg_utils.py:2664] This model does not officially support disabling chunked prefill. Disabling this manually may cause the engine to crash or produce incorrect outputs. +INFO 09-23 17:31:48 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +INFO 09-23 17:31:48 [stage_runtime.py:771] [stage_init] Stage-0 set runtime devices: 0 +W0923 17:31:51.896000 2301241 .venvs/omni-cpu/lib/python3.12/site-packages/torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +W0923 17:31:51.921000 2301241 .venvs/omni-cpu/lib/python3.12/site-packages/torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +WARNING 09-23 17:31:53 [importing.py:65] Triton is installed, but doesn't include CPU backend. Disabling Triton. +INFO 09-23 17:31:53 [importing.py:88] Triton not installed or not compatible; certain GPU-related functions will not be available. +INFO 09-23 17:31:53 [patch.py:252] NVFP4 W4A4 weight_scale NaN-clamp: installed. +INFO 09-23 17:31:54 [patch.py:503] inductor factorable-divisibility patch: installed. +INFO 09-23 17:31:54 [patch.py:633] CPU AOT compile-cache load shim installed: compiled models are reused across engine starts instead of being recompiled. +INFO 09-23 17:31:54 [patch.py:743] CPU weight-load memory release installed (set VLLM_OMNI_CPU_RELEASE_MEMORY=0 to disable). +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:31:54 [core.py:122] Initializing a V1 LLM engine (v0.28.0) with config: model='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', speculative_config=None, tokenizer='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=2048, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=None, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False, jit_monitor_mode='warn', jit_monitor_verbose=False), seed=0, served_model_name=/home/zhout/project/edge_infer/models/MiniCPM-o-4_5, enable_prefix_caching=False, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_vision_items_per_batch': 0, 'encoder_cudagraph_max_frames_per_batch': None, 'compile_sizes': None, 'compile_ranges_endpoints': [2048], 'inductor_compile_config': {'enable_auto_functionalized_v2': False}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'enable_qk_norm_rope_fusion': False, 'fuse_rope_kvcache_cat_mla': False, 'fuse_act_padding': False, 'fuse_qk_norm_rope_kvcache': False}, 'max_cudagraph_capture_size': None, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']), enable_flashinfer_autotune=True, enable_cutedsl_warmup=True, enable_jit_warmup=True, enable_bf16x3_router_gemm=False, moe_backend='auto', linear_backend='auto') +[W923 17:31:55.592331371 utils.cpp:68] Warning: NUMA binding: Using MEMBIND policy for memory allocation on the NUMA nodes (0). Memory allocations will be strictly bound to these NUMA nodes. (function init_cpu_memory_env) +(StageEngineCoreProc_stage0_replica0 pid=2301241) WARNING 09-23 17:31:55 [vllm.py:652] Model Runner V2 requires Triton; using the V1 model runner instead. +(StageEngineCoreProc_stage0_replica0 pid=2301241) WARNING 09-23 17:31:55 [cpu_worker.py:127] libiomp is not found in LD_PRELOAD. For best performance, please follow the section `set LD_PRELOAD` in https://docs.vllm.ai/en/latest/getting_started/installation/cpu/ to setup required pre-loaded libraries. +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:31:55 [parallel_state.py:1638] world_size=1 rank=0 local_rank=0 distributed_init_method=file:///tmp/vllm_dist_1280a2b851d74b6494f5a36dd3bff3ba backend=gloo +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:31:55 [parallel_state.py:1982] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A, EPLB rank N/A +(StageEngineCoreProc_stage0_replica0 pid=2301241) WARNING 09-23 17:31:55 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2301241) [transformers] `MiniCPMOProcessor` defines `image_processor_class = 'AutoImageProcessor'`, which is deprecated. Register the correct mapping in `AutoImageProcessor` instead. +(StageEngineCoreProc_stage0_replica0 pid=2301241) [transformers] Requested torchvision backend is not available. Falling back to pil backend. +(StageEngineCoreProc_stage0_replica0 pid=2301241) [transformers] `MiniCPMOProcessor` defines `feature_extractor_class = 'WhisperFeatureExtractor'`, which is deprecated. Register the correct mapping in `AutoFeatureExtractor` instead. +(StageEngineCoreProc_stage0_replica0 pid=2301241) WARNING 09-23 17:31:58 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2301241) WARNING 09-23 17:31:58 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2301241) WARNING 09-23 17:31:58 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:31:58 [cpu_model_runner.py:131] Starting to load model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5... +(StageEngineCoreProc_stage0_replica0 pid=2301241) WARNING 09-23 17:31:58 [vllm.py:1285] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none +(StageEngineCoreProc_stage0_replica0 pid=2301241) WARNING 09-23 17:31:58 [vllm.py:1354] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:31:58 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:31:58 [compilation.py:329] Enabled custom fusions: norm_quant, act_quant +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:32:01 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:32:01 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:32:01 [selector.py:217] Using HND KV cache layout for CPU_ATTN backend. +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:32:06 [weight_utils.py:858] Filesystem type for checkpoints: EXT4. Checkpoint size: 17.46 GiB. Available RAM: 25.88 GiB. +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:32:06 [weight_utils.py:881] Auto-prefetch is disabled because the filesystem (EXT4) is not a recognized network FS (NFS/Lustre). If you want to force prefetching, start vLLM with --safetensors-load-strategy=prefetch. +(StageEngineCoreProc_stage0_replica0 pid=2301241) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 20461 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:32:22 [cpu_worker.py:255] Explicitly set (1.0/30.91) GiB for KV cache on node 0. +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:32:22 [kv_cache_utils.py:1869] GPU KV cache size: 7,168 tokens, Maximum concurrency for 2,048 tokens per request: 3.50x +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:32:22 [memory.py:91] Released 0 MiB after warm-up (anonymous RSS 21469 -> 21469 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:32:22 [core.py:354] init engine (profile, create kv cache, warmup model) took 0.23 s +(StageEngineCoreProc_stage0_replica0 pid=2301241) WARNING 09-23 17:32:22 [scheduler.py:182] Using custom scheduler class vllm_omni.core.sched.omni_ar_scheduler.OmniARAsyncScheduler. This scheduler interface is not public and compatibility may not be maintained. If you have subclassed Scheduler instead of AsyncScheduler, you will see degraded performance due to async scheduling being disabled. +(StageEngineCoreProc_stage0_replica0 pid=2301241) WARNING 09-23 17:32:22 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2301241) WARNING 09-23 17:32:23 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:32:23 [factory.py:46] Created connector: SharedMemoryConnector +(StageEngineCoreProc_stage0_replica0 pid=2301241) INFO 09-23 17:32:23 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +INFO 09-23 17:32:23 [stage_runtime.py:871] [StageRuntime] Stage 0 engine startup completed +INFO 09-23 17:32:23 [stage_engine_core_client.py:159] [StageEngineCoreClient] stage-0 [rep-0] initializing EngineCore +INFO 09-23 17:32:23 [stage_engine_core_client.py:215] [StageEngineCoreClient] stage-0 [rep-0] EngineCore running +INFO 09-23 17:32:23 [stage_runtime.py:886] [StageRuntime] Stage 0 initialized +INFO 09-23 17:32:23 [stage_runtime.py:771] [stage_init] Stage-1 set runtime devices: 0 +W0923 17:32:29.931000 2301347 .venvs/omni-cpu/lib/python3.12/site-packages/torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +W0923 17:32:29.964000 2301347 .venvs/omni-cpu/lib/python3.12/site-packages/torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +WARNING 09-23 17:32:31 [importing.py:65] Triton is installed, but doesn't include CPU backend. Disabling Triton. +INFO 09-23 17:32:31 [importing.py:88] Triton not installed or not compatible; certain GPU-related functions will not be available. +INFO 09-23 17:32:32 [patch.py:252] NVFP4 W4A4 weight_scale NaN-clamp: installed. +INFO 09-23 17:32:32 [patch.py:503] inductor factorable-divisibility patch: installed. +INFO 09-23 17:32:32 [patch.py:633] CPU AOT compile-cache load shim installed: compiled models are reused across engine starts instead of being recompiled. +INFO 09-23 17:32:32 [patch.py:743] CPU weight-load memory release installed (set VLLM_OMNI_CPU_RELEASE_MEMORY=0 to disable). +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:33 [core.py:122] Initializing a V1 LLM engine (v0.28.0) with config: model='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', speculative_config=None, tokenizer='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=512, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=None, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False, jit_monitor_mode='warn', jit_monitor_verbose=False), seed=0, served_model_name=/home/zhout/project/edge_infer/models/MiniCPM-o-4_5, enable_prefix_caching=False, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_vision_items_per_batch': 0, 'encoder_cudagraph_max_frames_per_batch': None, 'compile_sizes': None, 'compile_ranges_endpoints': [512], 'inductor_compile_config': {'enable_auto_functionalized_v2': False}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'enable_qk_norm_rope_fusion': False, 'fuse_rope_kvcache_cat_mla': False, 'fuse_act_padding': False, 'fuse_qk_norm_rope_kvcache': False}, 'max_cudagraph_capture_size': None, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']), enable_flashinfer_autotune=True, enable_cutedsl_warmup=True, enable_jit_warmup=True, enable_bf16x3_router_gemm=False, moe_backend='auto', linear_backend='auto') +[W923 17:32:34.452742478 utils.cpp:68] Warning: NUMA binding: Using MEMBIND policy for memory allocation on the NUMA nodes (0). Memory allocations will be strictly bound to these NUMA nodes. (function init_cpu_memory_env) +(StageEngineCoreProc_stage1_replica0 pid=2301347) WARNING 09-23 17:32:34 [vllm.py:652] Model Runner V2 requires Triton; using the V1 model runner instead. +(StageEngineCoreProc_stage1_replica0 pid=2301347) WARNING 09-23 17:32:34 [cpu_worker.py:127] libiomp is not found in LD_PRELOAD. For best performance, please follow the section `set LD_PRELOAD` in https://docs.vllm.ai/en/latest/getting_started/installation/cpu/ to setup required pre-loaded libraries. +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:34 [parallel_state.py:1638] world_size=1 rank=0 local_rank=0 distributed_init_method=file:///tmp/vllm_dist_278a082a38b548ad9e3b89db9b034b71 backend=gloo +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:34 [parallel_state.py:1982] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A, EPLB rank N/A +(StageEngineCoreProc_stage1_replica0 pid=2301347) WARNING 09-23 17:32:34 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2301347) [transformers] `MiniCPMOProcessor` defines `image_processor_class = 'AutoImageProcessor'`, which is deprecated. Register the correct mapping in `AutoImageProcessor` instead. +(StageEngineCoreProc_stage1_replica0 pid=2301347) [transformers] Requested torchvision backend is not available. Falling back to pil backend. +(StageEngineCoreProc_stage1_replica0 pid=2301347) [transformers] `MiniCPMOProcessor` defines `feature_extractor_class = 'WhisperFeatureExtractor'`, which is deprecated. Register the correct mapping in `AutoFeatureExtractor` instead. +(StageEngineCoreProc_stage1_replica0 pid=2301347) [transformers] Image processor MiniCPMVImageProcessor: kwargs ['max_slice_nums'] were applied for backward compatibility. To avoid this warning, add them to valid_kwargs: create a custom TypedDict extending ImagesKwargs with these keys and set it as the `valid_kwargs` class attribute. +(StageEngineCoreProc_stage1_replica0 pid=2301347) WARNING 09-23 17:32:42 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2301347) WARNING 09-23 17:32:42 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2301347) WARNING 09-23 17:32:43 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:43 [factory.py:46] Created connector: SharedMemoryConnector +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:43 [cpu_model_runner.py:131] Starting to load model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5... +(StageEngineCoreProc_stage1_replica0 pid=2301347) WARNING 09-23 17:32:43 [vllm.py:1285] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none +(StageEngineCoreProc_stage1_replica0 pid=2301347) WARNING 09-23 17:32:43 [vllm.py:1354] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:43 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:43 [compilation.py:329] Enabled custom fusions: norm_quant, act_quant +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:43 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:43 [selector.py:217] Using HND KV cache layout for CPU_ATTN backend. +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:43 [weight_utils.py:858] Filesystem type for checkpoints: EXT4. Checkpoint size: 17.46 GiB. Available RAM: 6.68 GiB. +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:43 [weight_utils.py:888] Auto-prefetch is disabled because the filesystem (EXT4) is not a recognized network FS (NFS/Lustre) and the checkpoint size (17.46 GiB) exceeds 90% of available RAM (6.68 GiB). +(StageEngineCoreProc_stage1_replica0 pid=2301347) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 1457 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:46 [cpu_worker.py:255] Explicitly set (1.0/30.91) GiB for KV cache on node 0. +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:46 [kv_cache_utils.py:1869] GPU KV cache size: 17,408 tokens, Maximum concurrency for 512 tokens per request: 34.00x +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:47 [memory.py:91] Released 0 MiB after warm-up (anonymous RSS 2479 -> 2479 MiB) via ['libc.so.6:malloc_trim', 'libtcmalloc_minimal.so.4:MallocExtension_ReleaseFreeMemory'] +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:47 [core.py:354] init engine (profile, create kv cache, warmup model) took 0.40 s +(StageEngineCoreProc_stage1_replica0 pid=2301347) WARNING 09-23 17:32:47 [scheduler.py:182] Using custom scheduler class vllm_omni.core.sched.omni_ar_scheduler.OmniARAsyncScheduler. This scheduler interface is not public and compatibility may not be maintained. If you have subclassed Scheduler instead of AsyncScheduler, you will see degraded performance due to async scheduling being disabled. +(StageEngineCoreProc_stage1_replica0 pid=2301347) WARNING 09-23 17:32:47 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2301347) WARNING 09-23 17:32:47 [cpu_worker.py:153] CPU backend doesn't allow to use `torch.set_num_threads` after the thread binding, skip it. +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:47 [factory.py:46] Created connector: SharedMemoryConnector +(StageEngineCoreProc_stage1_replica0 pid=2301347) INFO 09-23 17:32:47 [kernel.py:308] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) +INFO 09-23 17:32:47 [stage_runtime.py:871] [StageRuntime] Stage 1 engine startup completed +INFO 09-23 17:32:47 [stage_engine_core_client.py:159] [StageEngineCoreClient] stage-1 [rep-0] initializing EngineCore +INFO 09-23 17:32:47 [stage_engine_core_client.py:215] [StageEngineCoreClient] stage-1 [rep-0] EngineCore running +INFO 09-23 17:32:47 [stage_runtime.py:886] [StageRuntime] Stage 1 initialized +INFO 09-23 17:32:47 [stage_runtime.py:771] [stage_init] Stage-2 set runtime devices: 0 +W0923 17:32:53.769000 2301454 .venvs/omni-cpu/lib/python3.12/site-packages/torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +W0923 17:32:53.808000 2301454 .venvs/omni-cpu/lib/python3.12/site-packages/torch/utils/_pytree.py:630] is an Enum subclass and is now natively supported by torch.compile as an opaque value type. Calling register_constant() on Enum subclasses is deprecated and will be an error in a future release. +WARNING 09-23 17:32:55 [importing.py:65] Triton is installed, but doesn't include CPU backend. Disabling Triton. +INFO 09-23 17:32:55 [importing.py:88] Triton not installed or not compatible; certain GPU-related functions will not be available. +INFO 09-23 17:32:56 [patch.py:252] NVFP4 W4A4 weight_scale NaN-clamp: installed. +INFO 09-23 17:32:56 [patch.py:503] inductor factorable-divisibility patch: installed. +INFO 09-23 17:32:56 [patch.py:633] CPU AOT compile-cache load shim installed: compiled models are reused across engine starts instead of being recompiled. +INFO 09-23 17:32:56 [patch.py:743] CPU weight-load memory release installed (set VLLM_OMNI_CPU_RELEASE_MEMORY=0 to disable). +(StageEngineCoreProc_stage2_replica0 pid=2301454) INFO 09-23 17:32:57 [core.py:122] Initializing a V1 LLM engine (v0.28.0) with config: model='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', speculative_config=None, tokenizer='/home/zhout/project/edge_infer/models/MiniCPM-o-4_5', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=4096, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=None, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cpu, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False, jit_monitor_mode='warn', jit_monitor_verbose=False), seed=0, served_model_name=/home/zhout/project/edge_infer/models/MiniCPM-o-4_5, enable_prefix_caching=False, enable_chunked_prefill=False, pooler_config=None, compilation_config={'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_vision_items_per_batch': 0, 'encoder_cudagraph_max_frames_per_batch': None, 'compile_sizes': None, 'compile_ranges_endpoints': [4096], 'inductor_compile_config': {'enable_auto_functionalized_v2': False}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'enable_qk_norm_rope_fusion': False, 'fuse_rope_kvcache_cat_mla': False, 'fuse_act_padding': False, 'fuse_qk_norm_rope_kvcache': False}, 'max_cudagraph_capture_size': None, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']), enable_flashinfer_autotune=True, enable_cutedsl_warmup=True, enable_jit_warmup=True, enable_bf16x3_router_gemm=False, moe_backend='auto', linear_backend='auto') +[W923 17:32:57.791689740 utils.cpp:68] Warning: NUMA binding: Using MEMBIND policy for memory allocation on the NUMA nodes (0). Memory allocations will be strictly bound to these NUMA nodes. (function init_cpu_memory_env) +(StageEngineCoreProc_stage2_replica0 pid=2301454) WARNING 09-23 17:32:57 [vllm.py:652] Model Runner V2 requires Triton; using the V1 model runner instead. +(StageEngineCoreProc_stage2_replica0 pid=2301454) WARNING 09-23 17:32:57 [cpu_worker.py:127] libiomp is not found in LD_PRELOAD. For best performance, please follow the section `set LD_PRELOAD` in https://docs.vllm.ai/en/latest/getting_started/installation/cpu/ to setup required pre-loaded libraries. +(StageEngineCoreProc_stage2_replica0 pid=2301454) INFO 09-23 17:32:57 [parallel_state.py:1638] world_size=1 rank=0 local_rank=0 distributed_init_method=file:///tmp/vllm_dist_596872673f5a47ea97847f3bf2204f58 backend=gloo +(StageEngineCoreProc_stage2_replica0 pid=2301454) INFO 09-23 17:32:57 [parallel_state.py:1982] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A, EPLB rank N/A +(StageEngineCoreProc_stage2_replica0 pid=2301454) INFO 09-23 17:32:57 [factory.py:46] Created connector: SharedMemoryConnector +(StageEngineCoreProc_stage2_replica0 pid=2301454) INFO 09-23 17:32:57 [cpu_model_runner.py:131] Starting to load model /home/zhout/project/edge_infer/models/MiniCPM-o-4_5... +(StageEngineCoreProc_stage2_replica0 pid=2301454) INFO 09-23 17:32:57 [weight_utils.py:858] Filesystem type for checkpoints: EXT4. Checkpoint size: 17.46 GiB. Available RAM: 4.76 GiB. +(StageEngineCoreProc_stage2_replica0 pid=2301454) INFO 09-23 17:32:57 [weight_utils.py:888] Auto-prefetch is disabled because the filesystem (EXT4) is not a recognized network FS (NFS/Lustre) and the checkpoint size (17.46 GiB) exceeds 90% of available RAM (4.76 GiB). +(StageEngineCoreProc_stage2_replica0 pid=2301454) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 + main(args) + File "/home/zhout/project/edge_infer/vllm-omni-edge/examples/offline_inference/minicpmo/end2end.py", line 283, in main + omni = Omni(**omni_kwargs) + ^^^^^^^^^^^^^^^^^^^ + File "/home/zhout/project/edge_infer/vllm-omni/vllm_omni/entrypoints/omni_base.py", line 223, in __init__ + self.engine = AsyncOmniEngine( + ^^^^^^^^^^^^^^^^ + File "/home/zhout/project/edge_infer/vllm-omni/vllm_omni/engine/async_omni_engine.py", line 301, in __init__ + self._wait_for_orchestrator_init(startup_future, startup_timeout) + File "/home/zhout/project/edge_infer/vllm-omni/vllm_omni/engine/async_omni_engine.py", line 534, in _wait_for_orchestrator_init + startup_future.result( + File "/home/zhout/.local/share/uv/python/cpython-3.12.13-linux-x86_64-gnu/lib/python3.12/concurrent/futures/_base.py", line 456, in result + return self.__get_result() + ^^^^^^^^^^^^^^^^^^^ + File "/home/zhout/.local/share/uv/python/cpython-3.12.13-linux-x86_64-gnu/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result + raise self._exception +RuntimeError: Orchestrator initialization failed: Engine core initialization failed. See root cause above. 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