INFO 07-06 02:46:12 [__init__.py:239] Automatically detected platform cuda. INFO 07-06 02:46:14 [config.py:209] Replacing legacy 'type' key with 'rope_type' INFO 07-06 02:46:14 [config.py:2968] Downcasting torch.float32 to torch.float16. INFO 07-06 02:46:21 [config.py:717] This model supports multiple tasks: {'generate', 'embed', 'classify', 'score', 'reward'}. Defaulting to 'generate'. INFO 07-06 02:46:21 [config.py:1770] Defaulting to use mp for distributed inference INFO 07-06 02:46:21 [config.py:2003] Chunked prefill is enabled with max_num_batched_tokens=16384. INFO 07-06 02:46:22 [core.py:58] Initializing a V1 LLM engine (v0.8.5.post1) with config: model='./merged1/phi_linear_7', speculative_config=None, tokenizer='./merged1/phi_linear_7', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.float16, max_seq_len=2048, download_dir=None, load_format=auto, tensor_parallel_size=4, pipeline_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto, device_config=cuda, decoding_config=DecodingConfig(guided_decoding_backend='auto', reasoning_backend=None), observability_config=ObservabilityConfig(show_hidden_metrics=False, otlp_traces_endpoint=None, collect_model_forward_time=False, collect_model_execute_time=False), seed=None, served_model_name=./merged1/phi_linear_7, num_scheduler_steps=1, multi_step_stream_outputs=True, enable_prefix_caching=True, chunked_prefill_enabled=True, use_async_output_proc=True, disable_mm_preprocessor_cache=False, mm_processor_kwargs=None, pooler_config=None, compilation_config={"level":3,"custom_ops":["none"],"splitting_ops":["vllm.unified_attention","vllm.unified_attention_with_output"],"use_inductor":true,"compile_sizes":[],"use_cudagraph":true,"cudagraph_num_of_warmups":1,"cudagraph_capture_sizes":[512,504,496,488,480,472,464,456,448,440,432,424,416,408,400,392,384,376,368,360,352,344,336,328,320,312,304,296,288,280,272,264,256,248,240,232,224,216,208,200,192,184,176,168,160,152,144,136,128,120,112,104,96,88,80,72,64,56,48,40,32,24,16,8,4,2,1],"max_capture_size":512} WARNING 07-06 02:46:22 [multiproc_worker_utils.py:306] Reducing Torch parallelism from 128 threads to 1 to avoid unnecessary CPU contention. Set OMP_NUM_THREADS in the external environment to tune this value as needed. INFO 07-06 02:46:22 [shm_broadcast.py:266] vLLM message queue communication handle: Handle(local_reader_ranks=[0, 1, 2, 3], buffer_handle=(4, 10485760, 10, 'psm_ce4c166f'), local_subscribe_addr='ipc:///tmp/9c8d640e-8d6e-4ee8-b0ef-db2baef5e786', remote_subscribe_addr=None, remote_addr_ipv6=False) WARNING 07-06 02:46:22 [utils.py:2522] Methods determine_num_available_blocks,device_config,get_cache_block_size_bytes,initialize_cache not implemented in (VllmWorker rank=1 pid=3940567) INFO 07-06 02:46:22 [shm_broadcast.py:266] vLLM message queue communication handle: Handle(local_reader_ranks=[0], buffer_handle=(1, 10485760, 10, 'psm_16defaa0'), local_subscribe_addr='ipc:///tmp/935be012-6f66-4106-8bc9-e7e31a3aa51c', remote_subscribe_addr=None, remote_addr_ipv6=False) WARNING 07-06 02:46:22 [utils.py:2522] Methods determine_num_available_blocks,device_config,get_cache_block_size_bytes,initialize_cache not implemented in (VllmWorker rank=0 pid=3940566) INFO 07-06 02:46:22 [shm_broadcast.py:266] vLLM message queue communication handle: Handle(local_reader_ranks=[0], buffer_handle=(1, 10485760, 10, 'psm_ff4c5b18'), local_subscribe_addr='ipc:///tmp/31fd90f4-a7d7-4de2-ae6a-559c689da219', remote_subscribe_addr=None, remote_addr_ipv6=False) WARNING 07-06 02:46:22 [utils.py:2522] Methods determine_num_available_blocks,device_config,get_cache_block_size_bytes,initialize_cache not implemented in WARNING 07-06 02:46:22 [utils.py:2522] Methods determine_num_available_blocks,device_config,get_cache_block_size_bytes,initialize_cache not implemented in (VllmWorker rank=2 pid=3940568) INFO 07-06 02:46:23 [shm_broadcast.py:266] vLLM message queue communication handle: Handle(local_reader_ranks=[0], buffer_handle=(1, 10485760, 10, 'psm_b27dd7df'), local_subscribe_addr='ipc:///tmp/9d20279d-b32d-4cb7-8a6a-b30af9f5c77e', remote_subscribe_addr=None, remote_addr_ipv6=False) (VllmWorker rank=3 pid=3940569) INFO 07-06 02:46:23 [shm_broadcast.py:266] vLLM message queue communication handle: Handle(local_reader_ranks=[0], buffer_handle=(1, 10485760, 10, 'psm_e1a03c9e'), local_subscribe_addr='ipc:///tmp/4b451eca-316d-4280-9087-2bf463e45cb4', remote_subscribe_addr=None, remote_addr_ipv6=False) (VllmWorker rank=1 pid=3940567) INFO 07-06 02:46:24 [utils.py:1055] Found nccl from library libnccl.so.2 (VllmWorker rank=0 pid=3940566) INFO 07-06 02:46:24 [utils.py:1055] Found nccl from library libnccl.so.2 (VllmWorker rank=1 pid=3940567) INFO 07-06 02:46:24 [pynccl.py:69] vLLM is using nccl==2.21.5 (VllmWorker rank=0 pid=3940566) INFO 07-06 02:46:24 [pynccl.py:69] vLLM is using nccl==2.21.5 (VllmWorker rank=3 pid=3940569) INFO 07-06 02:46:24 [utils.py:1055] Found nccl from library libnccl.so.2 (VllmWorker rank=2 pid=3940568) INFO 07-06 02:46:24 [utils.py:1055] Found nccl from library libnccl.so.2 (VllmWorker rank=2 pid=3940568) INFO 07-06 02:46:24 [pynccl.py:69] vLLM is using nccl==2.21.5 (VllmWorker rank=3 pid=3940569) INFO 07-06 02:46:24 [pynccl.py:69] vLLM is using nccl==2.21.5 (VllmWorker rank=3 pid=3940569) WARNING 07-06 02:46:25 [custom_all_reduce.py:136] Custom allreduce is disabled because it's not supported on more than two PCIe-only GPUs. To silence this warning, specify disable_custom_all_reduce=True explicitly. (VllmWorker rank=2 pid=3940568) WARNING 07-06 02:46:25 [custom_all_reduce.py:136] Custom allreduce is disabled because it's not supported on more than two PCIe-only GPUs. To silence this warning, specify disable_custom_all_reduce=True explicitly. (VllmWorker rank=1 pid=3940567) WARNING 07-06 02:46:25 [custom_all_reduce.py:136] Custom allreduce is disabled because it's not supported on more than two PCIe-only GPUs. To silence this warning, specify disable_custom_all_reduce=True explicitly. (VllmWorker rank=0 pid=3940566) WARNING 07-06 02:46:25 [custom_all_reduce.py:136] Custom allreduce is disabled because it's not supported on more than two PCIe-only GPUs. To silence this warning, specify disable_custom_all_reduce=True explicitly. (VllmWorker rank=0 pid=3940566) INFO 07-06 02:46:25 [shm_broadcast.py:266] vLLM message queue communication handle: Handle(local_reader_ranks=[1, 2, 3], buffer_handle=(3, 4194304, 6, 'psm_6fbe7734'), local_subscribe_addr='ipc:///tmp/0c9267d0-be15-4f44-87c6-74ef0054aa0f', remote_subscribe_addr=None, remote_addr_ipv6=False) (VllmWorker rank=3 pid=3940569) INFO 07-06 02:46:25 [parallel_state.py:1004] rank 3 in world size 4 is assigned as DP rank 0, PP rank 0, TP rank 3 (VllmWorker rank=2 pid=3940568) INFO 07-06 02:46:25 [parallel_state.py:1004] rank 2 in world size 4 is assigned as DP rank 0, PP rank 0, TP rank 2 (VllmWorker rank=1 pid=3940567) INFO 07-06 02:46:25 [parallel_state.py:1004] rank 1 in world size 4 is assigned as DP rank 0, PP rank 0, TP rank 1 (VllmWorker rank=0 pid=3940566) INFO 07-06 02:46:25 [parallel_state.py:1004] rank 0 in world size 4 is assigned as DP rank 0, PP rank 0, TP rank 0 (VllmWorker rank=3 pid=3940569) INFO 07-06 02:46:25 [cuda.py:221] Using Flash Attention backend on V1 engine. (VllmWorker rank=2 pid=3940568) INFO 07-06 02:46:25 [cuda.py:221] Using Flash Attention backend on V1 engine. (VllmWorker rank=3 pid=3940569) WARNING 07-06 02:46:25 [topk_topp_sampler.py:69] FlashInfer is not available. Falling back to the PyTorch-native implementation of top-p & top-k sampling. For the best performance, please install FlashInfer. (VllmWorker rank=2 pid=3940568) WARNING 07-06 02:46:25 [topk_topp_sampler.py:69] FlashInfer is not available. Falling back to the PyTorch-native implementation of top-p & top-k sampling. For the best performance, please install FlashInfer. (VllmWorker rank=0 pid=3940566) INFO 07-06 02:46:25 [cuda.py:221] Using Flash Attention backend on V1 engine. (VllmWorker rank=1 pid=3940567) INFO 07-06 02:46:25 [cuda.py:221] Using Flash Attention backend on V1 engine. (VllmWorker rank=0 pid=3940566) WARNING 07-06 02:46:25 [topk_topp_sampler.py:69] FlashInfer is not available. Falling back to the PyTorch-native implementation of top-p & top-k sampling. For the best performance, please install FlashInfer. (VllmWorker rank=1 pid=3940567) WARNING 07-06 02:46:25 [topk_topp_sampler.py:69] FlashInfer is not available. Falling back to the PyTorch-native implementation of top-p & top-k sampling. For the best performance, please install FlashInfer. (VllmWorker rank=3 pid=3940569) INFO 07-06 02:46:25 [gpu_model_runner.py:1329] Starting to load model ./merged1/phi_linear_7... (VllmWorker rank=2 pid=3940568) INFO 07-06 02:46:25 [gpu_model_runner.py:1329] Starting to load model ./merged1/phi_linear_7... (VllmWorker rank=1 pid=3940567) INFO 07-06 02:46:25 [gpu_model_runner.py:1329] Starting to load model ./merged1/phi_linear_7... (VllmWorker rank=0 pid=3940566) INFO 07-06 02:46:25 [gpu_model_runner.py:1329] Starting to load model ./merged1/phi_linear_7... (VllmWorker rank=0 pid=3940566) INFO 07-06 02:46:39 [loader.py:458] Loading weights took 13.74 seconds (VllmWorker rank=2 pid=3940568) INFO 07-06 02:46:39 [loader.py:458] Loading weights took 13.87 seconds (VllmWorker rank=3 pid=3940569) INFO 07-06 02:46:39 [loader.py:458] Loading weights took 13.86 seconds (VllmWorker rank=1 pid=3940567) INFO 07-06 02:46:39 [loader.py:458] Loading weights took 13.83 seconds (VllmWorker rank=3 pid=3940569) INFO 07-06 02:46:39 [gpu_model_runner.py:1347] Model loading took 1.8196 GiB and 14.052956 seconds (VllmWorker rank=2 pid=3940568) INFO 07-06 02:46:39 [gpu_model_runner.py:1347] Model loading took 1.8196 GiB and 14.052767 seconds (VllmWorker rank=0 pid=3940566) INFO 07-06 02:46:39 [gpu_model_runner.py:1347] Model loading took 1.8196 GiB and 13.948024 seconds (VllmWorker rank=1 pid=3940567) INFO 07-06 02:46:39 [gpu_model_runner.py:1347] Model loading took 1.8196 GiB and 14.053611 seconds (VllmWorker rank=2 pid=3940568) INFO 07-06 02:46:45 [backends.py:420] Using cache directory: /home/jiangli/.cache/vllm/torch_compile_cache/39e4f38180/rank_2_0 for vLLM's torch.compile (VllmWorker rank=2 pid=3940568) INFO 07-06 02:46:45 [backends.py:430] Dynamo bytecode transform time: 5.58 s (VllmWorker rank=3 pid=3940569) INFO 07-06 02:46:45 [backends.py:420] Using cache directory: /home/jiangli/.cache/vllm/torch_compile_cache/39e4f38180/rank_3_0 for vLLM's torch.compile (VllmWorker rank=3 pid=3940569) INFO 07-06 02:46:45 [backends.py:430] Dynamo bytecode transform time: 5.62 s (VllmWorker rank=1 pid=3940567) INFO 07-06 02:46:45 [backends.py:420] Using cache directory: /home/jiangli/.cache/vllm/torch_compile_cache/39e4f38180/rank_1_0 for vLLM's torch.compile (VllmWorker rank=1 pid=3940567) INFO 07-06 02:46:45 [backends.py:430] Dynamo bytecode transform time: 5.71 s (VllmWorker rank=0 pid=3940566) INFO 07-06 02:46:45 [backends.py:420] Using cache directory: /home/jiangli/.cache/vllm/torch_compile_cache/39e4f38180/rank_0_0 for vLLM's torch.compile (VllmWorker rank=0 pid=3940566) INFO 07-06 02:46:45 [backends.py:430] Dynamo bytecode transform time: 5.79 s (VllmWorker rank=2 pid=3940568) INFO 07-06 02:46:49 [backends.py:136] Cache the graph of shape None for later use (VllmWorker rank=3 pid=3940569) INFO 07-06 02:46:49 [backends.py:136] Cache the graph of shape None for later use (VllmWorker rank=1 pid=3940567) INFO 07-06 02:46:50 [backends.py:136] Cache the graph of shape None for later use (VllmWorker rank=0 pid=3940566) INFO 07-06 02:46:50 [backends.py:136] Cache the graph of shape None for later use (VllmWorker rank=2 pid=3940568) INFO 07-06 02:47:11 [backends.py:148] Compiling a graph for general shape takes 25.07 s (VllmWorker rank=3 pid=3940569) INFO 07-06 02:47:11 [backends.py:148] Compiling a graph for general shape takes 25.20 s (VllmWorker rank=1 pid=3940567) INFO 07-06 02:47:11 [backends.py:148] Compiling a graph for general shape takes 25.04 s (VllmWorker rank=0 pid=3940566) INFO 07-06 02:47:11 [backends.py:148] Compiling a graph for general shape takes 25.13 s (VllmWorker rank=1 pid=3940567) INFO 07-06 02:47:33 [monitor.py:33] torch.compile takes 30.75 s in total (VllmWorker rank=3 pid=3940569) INFO 07-06 02:47:33 [monitor.py:33] torch.compile takes 30.81 s in total (VllmWorker rank=0 pid=3940566) INFO 07-06 02:47:33 [monitor.py:33] torch.compile takes 30.92 s in total (VllmWorker rank=2 pid=3940568) INFO 07-06 02:47:33 [monitor.py:33] torch.compile takes 30.65 s in total INFO 07-06 02:47:34 [kv_cache_utils.py:634] GPU KV cache size: 1,999,536 tokens INFO 07-06 02:47:34 [kv_cache_utils.py:637] Maximum concurrency for 2,048 tokens per request: 976.34x INFO 07-06 02:47:34 [kv_cache_utils.py:634] GPU KV cache size: 1,999,280 tokens INFO 07-06 02:47:34 [kv_cache_utils.py:637] Maximum concurrency for 2,048 tokens per request: 976.21x INFO 07-06 02:47:34 [kv_cache_utils.py:634] GPU KV cache size: 1,999,280 tokens INFO 07-06 02:47:34 [kv_cache_utils.py:637] Maximum concurrency for 2,048 tokens per request: 976.21x INFO 07-06 02:47:34 [kv_cache_utils.py:634] GPU KV cache size: 2,000,560 tokens INFO 07-06 02:47:34 [kv_cache_utils.py:637] Maximum concurrency for 2,048 tokens per request: 976.84x (VllmWorker rank=2 pid=3940568) INFO 07-06 02:48:05 [gpu_model_runner.py:1686] Graph capturing finished in 31 secs, took 3.00 GiB (VllmWorker rank=3 pid=3940569) INFO 07-06 02:48:05 [gpu_model_runner.py:1686] Graph capturing finished in 31 secs, took 3.00 GiB (VllmWorker rank=1 pid=3940567) INFO 07-06 02:48:05 [gpu_model_runner.py:1686] Graph capturing finished in 31 secs, took 3.00 GiB (VllmWorker rank=0 pid=3940566) INFO 07-06 02:48:05 [gpu_model_runner.py:1686] Graph capturing finished in 31 secs, took 3.00 GiB INFO 07-06 02:48:05 [core.py:159] init engine (profile, create kv cache, warmup model) took 85.74 seconds INFO 07-06 02:48:05 [core_client.py:439] Core engine process 0 ready. INFO 07-06 02:49:54 [importing.py:53] Triton module has been replaced with a placeholder. INFO 07-06 02:49:54 [__init__.py:239] Automatically detected platform cuda. | Task |Version| Metric |Value | |Stderr| |------------------|------:|---------------------|-----:|---|-----:| |all | |sem |0.8754|± |0.0195| | | |math_pass@1:1_samples|0.8782|± |0.0341| |mm\|arc_challenge\|0| 0|sem |0.9396|± |0.0122| |mm\|arc_easy\|0 | 0|sem |0.9662|± |0.0059| |mm\|commonsenseqa\|0| 0|sem |0.8438|± |0.0203| |mm\|gsm8k\|0 | 0|math_pass@1:1_samples|0.8814|± |0.0153| |mm\|math_500\|0 | 3|math_pass@1:1_samples|0.8750|± |0.0530| |mm\|truthfulqa\|0 | 0|sem |0.7521|± |0.0394|