The following have been reloaded with a version change: 1) GCCcore/.14.3.0 => GCCcore/14.3.0 Lmod is automatically replacing "GCC/14.3.0" with "nvidia-compilers/25.9-CUDA-13". Deactivating conda environment: /e/scratch/jureap59/feuer1/miniforge3/envs/otagent Activating RL environment: /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl Python executable: /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/bin/python Python path check: /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/bin/python [ray] RAY_TMPDIR=/tmp/ray/ray_630126 [triton_cache] Triton cache: /tmp/triton_cache_feuer1_630126 [triton_cache] TorchInductor cache: /tmp/torchinductor_cache_feuer1_630126 [proxy] ✓ Found proxychains binary at /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 [proxy] Setting up SSH tunnel to jpbl-s01-01 [proxy] SSH key: /e/home/jusers/feuer1/jupiter/.ssh/authorized_keys/id_ed25519_jsc [proxy] Tunnel port: 7003 [proxy] Node IP: 10.128.32.33 (workers will connect here) [proxy] ✓ SSH tunnel started successfully [proxy] ✓ Generated proxychains config at /e/home/jusers/feuer1/jupiter/.proxychains/proxychains_630126.conf [proxy] - Internal traffic (10.x.x.x, 172.x.x.x, 169.254.x.x) → DIRECT [proxy] - External traffic (internet) → PROXY via tunnel [proxy] ✓ Daytona timeout settings configured [proxy] Testing proxy connectivity... [proxychains] config file found: /e/home/jusers/feuer1/jupiter/.proxychains/proxychains_630126.conf [proxychains] preloading /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/lib/libproxychains4.so [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [proxy] ✓ Proxy connectivity test passed (huggingface.co reachable via wrapped binary) [proxy] ⚠ Tunnel not accessible at 10.128.32.33:7003 (workers may fail) [proxy] ✓ Proxy setup complete (using wrapped binary for Ray workers) [container_runtime] Using cloud backend: daytona (no local container setup) === Universal RL Training Runner === Config: /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/configs/ablation-pymethods2test-seqmean-arm0_rl_config.json Working directory: /e/scratch/jureap59/feuer1/OpenThoughts-Agent Python: /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/bin/python Python version: Python 3.12.12 UV_USE_IO_URING: 0 Proxy: DISABLED (direct internet or not configured) ======================================== === RLJobRunner: ablation-pymethods2test-seqmean-arm0 === [wandb_utils] Fixing permissions on: /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/wandb [wandb_utils] WandB directory ready: /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/wandb HF_TOKEN=****pDbg HF_HUB_CACHE=/e/data1/datasets/playground/ot-baf/hf_hub SUPABASE_URL=https://rpzmyuapoqilpghynmza.s... (direct Supabase config) Environment configured: TENSOR_PARALLEL_SIZE=1 NUM_INFERENCE_ENGINES=56 POLICY_NUM_NODES=14 WANDB_DIR=/e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/wandb Starting Ray cluster with 14 nodes, 4 GPUs/node Cleaning up existing Ray instances... === Starting Ray Cluster === Nodes: 14 GPUs per node: 4 CPUs per node: 288 Head node: jpbo-041-33 (10.128.32.33) Ray port: 6379 ============================ Starting Ray head on jpbo-041-33 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_head_jpbo-041-33.log)... Command: srun --export=ALL,VLLM_HOST_IP=10.128.32.33 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-041-33 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --head --node-ip-address=10.128.32.33 --port=6379 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 Started Ray head on jpbo-041-33 Starting Ray worker on jpbo-041-34 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-041-34.log)... Command: srun --export=ALL,VLLM_HOST_IP=10.128.32.34 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-041-34 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.32.33:6379 --node-ip-address=10.128.32.34 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 Started Ray worker 1 on jpbo-041-34 Starting Ray worker on jpbo-041-35 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-041-35.log)... Command: srun --export=ALL,VLLM_HOST_IP=10.128.32.35 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-041-35 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.32.33:6379 --node-ip-address=10.128.32.35 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 Started Ray worker 2 on jpbo-041-35 Starting Ray worker on jpbo-041-36 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-041-36.log)... Command: srun --export=ALL,VLLM_HOST_IP=10.128.32.36 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-041-36 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.32.33:6379 --node-ip-address=10.128.32.36 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 Started Ray worker 3 on jpbo-041-36 Starting Ray worker on jpbo-041-37 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-041-37.log)... Command: srun --export=ALL,VLLM_HOST_IP=10.128.32.37 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-041-37 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.32.33:6379 --node-ip-address=10.128.32.37 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 Started Ray worker 4 on jpbo-041-37 Starting Ray worker on jpbo-041-38 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-041-38.log)... Command: srun --export=ALL,VLLM_HOST_IP=10.128.32.38 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-041-38 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.32.33:6379 --node-ip-address=10.128.32.38 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 Started Ray worker 5 on jpbo-041-38 Starting Ray worker on jpbo-041-39 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-041-39.log)... Command: srun --export=ALL,VLLM_HOST_IP=10.128.32.39 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-041-39 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.32.33:6379 --node-ip-address=10.128.32.39 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 Started Ray worker 6 on jpbo-041-39 Starting Ray worker on jpbo-041-40 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-041-40.log)... Command: srun --export=ALL,VLLM_HOST_IP=10.128.32.40 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-041-40 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.32.33:6379 --node-ip-address=10.128.32.40 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 Started Ray worker 7 on jpbo-041-40 Starting Ray worker on jpbo-041-41 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-041-41.log)... Command: srun --export=ALL,VLLM_HOST_IP=10.128.32.41 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-041-41 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.32.33:6379 --node-ip-address=10.128.32.41 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 Started Ray worker 8 on jpbo-041-41 Starting Ray worker on jpbo-041-42 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-041-42.log)... Command: srun --export=ALL,VLLM_HOST_IP=10.128.32.42 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-041-42 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.32.33:6379 --node-ip-address=10.128.32.42 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 Started Ray worker 9 on jpbo-041-42 Starting Ray worker on jpbo-041-43 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-041-43.log)... Command: srun --export=ALL,VLLM_HOST_IP=10.128.32.43 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-041-43 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.32.33:6379 --node-ip-address=10.128.32.43 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 Started Ray worker 10 on jpbo-041-43 Starting Ray worker on jpbo-041-44 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-041-44.log)... Command: srun --export=ALL,VLLM_HOST_IP=10.128.32.44 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-041-44 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.32.33:6379 --node-ip-address=10.128.32.44 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 Started Ray worker 11 on jpbo-041-44 Starting Ray worker on jpbo-041-45 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-041-45.log)... Command: srun --export=ALL,VLLM_HOST_IP=10.128.32.45 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-041-45 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.32.33:6379 --node-ip-address=10.128.32.45 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 Started Ray worker 12 on jpbo-041-45 Starting Ray worker on jpbo-041-46 (logging to /e/data1/datasets/playground/ot-baf/experiments/_ray_logs/ray_worker_jpbo-041-46.log)... Command: srun --export=ALL,VLLM_HOST_IP=10.128.32.46 --nodes=1 --ntasks=1 --gres=gpu:4 --gpu-bind=none --overlap --cpu-bind=none -w jpbo-041-46 bash -c /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f "$PROXYCHAINS_CONF_FILE" ray start --address=10.128.32.33:6379 --node-ip-address=10.128.32.46 --num-gpus=4 --num-cpus=288 --block --object-store-memory=42949672960 Started Ray worker 13 on jpbo-041-46 Waiting for cluster (56 GPUs, 14 nodes)... Connecting to Ray at 10.128.32.33:6379 (expecting 14 nodes, 56.0 GPUs) Ray connection established, polling for resources... [Ray wait] nodes=14/14 GPUs=56.0/56.0 resources={'GPU': 56.0, 'memory': 10652272558080.0, 'accelerator_type:GH200': 14.0, 'object_store_memory': 601295421440.0, 'CPU': 4032.0, 'node:10.128.32.35': 1.0, 'node:10.128.32.45': 1.0, 'node:10.128.32.44': 1.0, 'node:10.128.32.38': 1.0, 'node:10.128.32.34': 1.0, 'node:10.128.32.46': 1.0, 'node:10.128.32.39': 1.0, 'node:10.128.32.41': 1.0, 'node:__internal_head__': 1.0, 'node:10.128.32.33': 1.0, 'node:10.128.32.40': 1.0, 'node:10.128.32.36': 1.0, 'node:10.128.32.37': 1.0, 'node:10.128.32.42': 1.0, 'node:10.128.32.43': 1.0} ✓ Ray cluster ready === Ray Cluster Ready === Address: 10.128.32.33:6379 Total GPUs: 56 ========================= Ray cluster ready at 10.128.32.33:6379 Total GPUs available: 56 [RLJobRunner] Pinggy check: url=False, token=False, needs_tunnel=False (agent=terminus-2, env=daytona) [RLJobRunner] No Pinggy tunnel needed, using local vLLM Running SkyRL: Python: /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/bin/python Entrypoint: examples.terminal_bench.entrypoints.main_tbench Args: 120 Hydra arguments Working dir: /e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train Using proxychains binary: /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 Executing command with srun: /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/bin/proxychains4 -f $PROXYCHAINS_CONF_FILE /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/bin/python -m examples.terminal_bench.entrypoints.main_tbench +terminal_bench_config=terminal_bench trainer.strategy=fsdp2 trainer.algorithm.advantage_estimator=rloo_n trainer.algorithm.use_kl_loss=false trainer.algorithm.kl_loss_coef=0.0 trainer.algorithm.eps_clip_low=0.2 trainer.algorithm.eps_clip_high=0.05 trainer.algorithm.loss_reduction=sequence_mean trainer.epochs=2 trainer.max_steps=80 trainer.update_epochs_per_batch=1 trainer.train_batch_size=64 trainer.policy_mini_batch_size=64 trainer.eval_batch_size=64 trainer.micro_forward_batch_size_per_gpu=4 trainer.micro_train_batch_size_per_gpu=1 trainer.max_prompt_length=999999 trainer.eval_interval=999999 trainer.eval_before_train=false trainer.ckpt_interval=2 trainer.resume_mode=latest trainer.hf_save_interval=5 ++trainer.hf_hub_repo_id=laion/ablation-pymethods2test-seqmean-arm0 ++trainer.hf_hub_private=false ++trainer.hf_hub_revision=main ++trainer.enable_db_registration=false trainer.project_name=OpenThoughts-Agent trainer.log_level=INFO trainer.tracker_commit_each_step=true trainer.logger=console trainer.run_name=ablation-pymethods2test-seqmean-arm0 trainer.ckpt_path=/e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/checkpoints trainer.export_path=/e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/exports trainer.policy.optimizer_config.lr=8e-6 trainer.policy.optimizer_config.weight_decay=0.0 trainer.policy.optimizer_config.adam_betas=[0.9,0.999] trainer.policy.optimizer_config.max_grad_norm=0.9 trainer.policy.fsdp_config.cpu_offload=false trainer.policy.fsdp_config.reshard_after_forward=true trainer.policy.fsdp_config.fsdp_size=4 trainer.policy.model.path=/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6 trainer.ref.fsdp_config.cpu_offload=false trainer.ref.fsdp_config.reshard_after_forward=true trainer.ref.fsdp_config.fsdp_size=4 trainer.placement.colocate_all=false trainer.placement.policy_num_nodes=2 trainer.placement.ref_num_nodes=2 trainer.placement.policy_num_gpus_per_node=4 trainer.placement.ref_num_gpus_per_node=4 trainer.fully_async.max_staleness_steps=16 trainer.fully_async.num_parallel_generation_workers=338 generator.backend=vllm generator.timeout_multiplier=1.0 generator.model_dtype=bfloat16 generator.inference_engine_tensor_parallel_size=1 generator.num_inference_engines=48 generator.n_samples_per_prompt=8 generator.eval_n_samples_per_prompt=8 generator.gpu_memory_utilization=0.75 generator.max_num_seqs=24 generator.max_num_batched_tokens=65536 generator.enable_prefix_caching=true generator.enable_chunked_prefill=true generator.run_engines_locally=true generator.weight_sync_backend=nccl generator.async_engine=true generator.batched=false generator.enable_http_endpoint=true generator.enable_ray_prometheus_stats=false generator.vllm_stats_interval=1 generator.append_eos_token_after_stop_str_in_multi_turn=true generator.max_turns=999999 generator.sampling_params.max_generate_length=4096 generator.sampling_params.temperature=0.7 generator.sampling_params.top_p=0.95 generator.sampling_params.top_k=20 ++generator.engine_init_kwargs.max_model_len=32768 ++generator.engine_init_kwargs.custom_chat_template_chat_completion_path=chat_templates/qwen3_thinking_acc.jinja2 ++generator.engine_init_kwargs.served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6 data.train_data=["/e/scratch/jureap59/feuer1/tasks/exp_rpt_pymethods2test-large"] data.val_data=[] +terminal_bench_config.trials_dir=/e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/trace_jobs +terminal_bench_config.harbor.name=terminus-2 +terminal_bench_config.harbor.max_episodes=999999 +terminal_bench_config.harbor.enable_summarize=false +terminal_bench_config.harbor.store_all_messages=true +terminal_bench_config.harbor.trajectory_config.raw_content=true +terminal_bench_config.harbor.enable_episode_logging=false +terminal_bench_config.harbor.record_terminal_session=false +terminal_bench_config.harbor.enable_pane_logging=false +terminal_bench_config.harbor.strict_json_parser=true +terminal_bench_config.harbor.interleaved_thinking=true +terminal_bench_config.harbor.extra_body.chat_template_kwargs.enable_thinking=true +terminal_bench_config.harbor.override_timeout_sec=900 +terminal_bench_config.harbor.override_cpus=1 +terminal_bench_config.harbor.override_memory_mb=2048 +terminal_bench_config.harbor.override_storage_mb=2048 +terminal_bench_config.harbor.auto_snapshot=true +terminal_bench_config.harbor.verifier_override_timeout_sec=120 +terminal_bench_config.harbor.max_retries=3 +terminal_bench_config.harbor.min_wait_sec=60.0 +terminal_bench_config.harbor.max_wait_sec=600.0 +terminal_bench_config.harbor.wait_multiplier=2.0 +terminal_bench_config.harbor.exclude_exceptions=["VerifierTimeoutError","VerifierRuntimeError","RewardFileNotFoundError","RewardFileEmptyError","VerifierOutputParseError"] +terminal_bench_config.harbor.n_concurrent_trials=675 +terminal_bench_config.harbor.log_level=INFO +terminal_bench_config.harbor.enable_reward_shaping=false +terminal_bench_config.harbor.enable_error_classification=true +terminal_bench_config.harbor.mask_exceptions=["DaytonaError","EnvironmentStartTimeoutError","NetworkError","ConnectionError","RewardFileNotFoundError","RewardFileEmptyError","AgentEnvironmentTimeoutError","ContextLengthExceededError"] +terminal_bench_config.harbor.default_error_treatment=zero +terminal_bench_config.harbor.passthrough_exceptions=["AgentTimeoutError"] +terminal_bench_config.harbor.zero_exceptions=[] +terminal_bench_config.model_info.max_input_tokens=32000 +terminal_bench_config.model_info.max_output_tokens=4096 +terminal_bench_config.archiving.enabled=false +terminal_bench_config.trace_upload.enabled=true +terminal_bench_config.trace_upload.repo_org=DCAgent +terminal_bench_config.trace_upload.episodes=last +terminal_bench_config.trace_upload.dataset_type=SFT +terminal_bench_config.trace_upload.cleanup=true [proxychains] config file found: /e/home/jusers/feuer1/jupiter/.proxychains/proxychains_630126.conf [proxychains] preloading /e/scratch/jureap59/feuer1/proxychains-ng-aarch64/lib/libproxychains4.so [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e 2026-06-07 02:20:53.422 | INFO | skyrl_train.utils.utils:prepare_runtime_environment:686 - Exporting wandb api key to ray runtime env 2026-06-07 02:20:53.423 | INFO | skyrl_train.utils.utils:prepare_runtime_environment:705 - Exporting RAY_ADDRESS to ray runtime env 2026-06-07 02:20:53.423 | INFO | skyrl_train.utils.utils:prepare_runtime_environment:730 - Exporting `NCCL_SOCKET_IFNAME` to ray runtime env: ib0 2026-06-07 02:20:53.423 | INFO | skyrl_train.utils.utils:prepare_runtime_environment:730 - Exporting `NCCL_SOCKET_FAMILY` to ray runtime env: AF_INET 2026-06-07 02:20:53.423 | INFO | skyrl_train.utils.utils:prepare_runtime_environment:730 - Exporting `NCCL_DEBUG` to ray runtime env: WARN 2026-06-07 02:20:53,423 INFO worker.py:1680 -- Using address 10.128.32.33:6379 set in the environment variable RAY_ADDRESS 2026-06-07 02:20:53,456 INFO worker.py:1821 -- Connecting to existing Ray cluster at address: 10.128.32.33:6379... 2026-06-07 02:20:53,467 INFO worker.py:2007 -- Connected to Ray cluster. /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/worker.py:2046: FutureWarning: Tip: In future versions of Ray, Ray will no longer override accelerator visible devices env var if num_gpus=0 or num_gpus=None (default). To enable this behavior and turn off this error message, set RAY_ACCEL_ENV_VAR_OVERRIDE_ON_ZERO=0 warnings.warn( (raylet, ip=10.128.32.37) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e 2026-06-07 02:20:55.689 | INFO | skyrl_train.utils.ppo_utils:sync_registries:546 - Synced registries to ray actor (skyrl_entrypoint pid=294281) 2026-06-07 02:21:02.936 | INFO  | skyrl_train.entrypoints.main_base:_configure_log_level:212 - SkyRL log level set to: INFO (raylet) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 17x across cluster] (Ray deduplicates logs by default. Set RAY_DEDUP_LOGS=0 to disable log deduplication, or see https://docs.ray.io/en/master/ray-observability/user-guides/configure-logging.html#log-deduplication for more options.) (skyrl_entrypoint pid=294281) The tokenizer you are loading from '/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. (skyrl_entrypoint pid=294281) 2026-06-07 02:21:03.364 | INFO  | examples.terminal_bench.dataset:_load_data_files:40 - Loading data from: /e/scratch/jureap59/feuer1/tasks/exp_rpt_pymethods2test-large (skyrl_entrypoint pid=294281) 2026-06-07 02:21:06.531 | INFO  | examples.terminal_bench.dataset:_load_data_files:50 - Found 5000 valid task directories out of 5000 total directories (skyrl_entrypoint pid=294281) 2026-06-07 02:21:06.532 | INFO  | examples.terminal_bench.dataset:__init__:27 - TerminalBenchTaskDataset initialized with 5000 task paths (skyrl_entrypoint pid=294281) 2026-06-07 02:21:06.545 | INFO  | skyrl_train.entrypoints.main_base:_setup_trainer:405 - data: (skyrl_entrypoint pid=294281) train_data: (skyrl_entrypoint pid=294281) - /e/scratch/jureap59/feuer1/tasks/exp_rpt_pymethods2test-large (skyrl_entrypoint pid=294281) val_data: [] (skyrl_entrypoint pid=294281) trainer: (skyrl_entrypoint pid=294281) placement: (skyrl_entrypoint pid=294281) colocate_all: false (skyrl_entrypoint pid=294281) colocate_policy_ref: true (skyrl_entrypoint pid=294281) policy_num_nodes: 2 (skyrl_entrypoint pid=294281) policy_num_gpus_per_node: 4 (skyrl_entrypoint pid=294281) critic_num_nodes: 1 (skyrl_entrypoint pid=294281) critic_num_gpus_per_node: 4 (skyrl_entrypoint pid=294281) ref_num_nodes: 2 (skyrl_entrypoint pid=294281) ref_num_gpus_per_node: 4 (skyrl_entrypoint pid=294281) policy_strict_spread_pg: false (skyrl_entrypoint pid=294281) policy_per_gpu_bundles: false (skyrl_entrypoint pid=294281) sequence_parallel_backend: ulysses (skyrl_entrypoint pid=294281) strategy: fsdp2 (skyrl_entrypoint pid=294281) policy: (skyrl_entrypoint pid=294281) model: (skyrl_entrypoint pid=294281) path: /e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6 (skyrl_entrypoint pid=294281) lora: (skyrl_entrypoint pid=294281) rank: 0 (skyrl_entrypoint pid=294281) alpha: 16 (skyrl_entrypoint pid=294281) dropout: 0 (skyrl_entrypoint pid=294281) lora_sync_path: /tmp/skyrl_lora_sync (skyrl_entrypoint pid=294281) target_modules: all-linear (skyrl_entrypoint pid=294281) exclude_modules: null (skyrl_entrypoint pid=294281) deepspeed_config: ${deepspeed_config.train} (skyrl_entrypoint pid=294281) optimizer_config: (skyrl_entrypoint pid=294281) optimizer: AdamW (skyrl_entrypoint pid=294281) lr: 8.0e-06 (skyrl_entrypoint pid=294281) adam_betas: (skyrl_entrypoint pid=294281) - 0.9 (skyrl_entrypoint pid=294281) - 0.999 (skyrl_entrypoint pid=294281) weight_decay: 0.0 (skyrl_entrypoint pid=294281) max_grad_norm: 0.9 (skyrl_entrypoint pid=294281) offload_after_step: true (skyrl_entrypoint pid=294281) num_warmup_steps: 0 (skyrl_entrypoint pid=294281) scheduler: constant_with_warmup (skyrl_entrypoint pid=294281) optimizer_kwargs: {} (skyrl_entrypoint pid=294281) fsdp_config: (skyrl_entrypoint pid=294281) cpu_offload: false (skyrl_entrypoint pid=294281) reshard_after_forward: true (skyrl_entrypoint pid=294281) fsdp_size: 4 (skyrl_entrypoint pid=294281) expert_model_parallel_size: 1 (skyrl_entrypoint pid=294281) expert_tensor_parallel_size: 1 (skyrl_entrypoint pid=294281) moe_token_dispatcher_type: alltoall (skyrl_entrypoint pid=294281) moe_router_replay: false (skyrl_entrypoint pid=294281) moe_grouped_gemm: false (skyrl_entrypoint pid=294281) ep_comm_backend: torch (skyrl_entrypoint pid=294281) deepep_num_sms: 20 (skyrl_entrypoint pid=294281) deepep_token_chunk_size: null (skyrl_entrypoint pid=294281) sequence_parallel_size: 1 (skyrl_entrypoint pid=294281) use_torch_compile: false (skyrl_entrypoint pid=294281) record_memory: false (skyrl_entrypoint pid=294281) megatron_config: (skyrl_entrypoint pid=294281) tensor_model_parallel_size: 1 (skyrl_entrypoint pid=294281) pipeline_model_parallel_size: 1 (skyrl_entrypoint pid=294281) context_parallel_size: 1 (skyrl_entrypoint pid=294281) expert_model_parallel_size: 1 (skyrl_entrypoint pid=294281) expert_tensor_parallel_size: null (skyrl_entrypoint pid=294281) ddp_config: (skyrl_entrypoint pid=294281) grad_reduce_in_fp32: true (skyrl_entrypoint pid=294281) overlap_grad_reduce: false (skyrl_entrypoint pid=294281) overlap_param_gather: false (skyrl_entrypoint pid=294281) average_in_collective: true (skyrl_entrypoint pid=294281) model_config_kwargs: {} (skyrl_entrypoint pid=294281) torch_profiler_config: (skyrl_entrypoint pid=294281) enable: false (skyrl_entrypoint pid=294281) ranks: [] (skyrl_entrypoint pid=294281) save_path: null (skyrl_entrypoint pid=294281) optimizer_config_kwargs: (skyrl_entrypoint pid=294281) overlap_cpu_optimizer_d2h_h2d: false (skyrl_entrypoint pid=294281) use_precision_aware_optimizer: false (skyrl_entrypoint pid=294281) optimizer_cpu_offload: false (skyrl_entrypoint pid=294281) optimizer_offload_fraction: 0.0 (skyrl_entrypoint pid=294281) transformer_config_kwargs: (skyrl_entrypoint pid=294281) recompute_granularity: full (skyrl_entrypoint pid=294281) recompute_modules: (skyrl_entrypoint pid=294281) - core_attn (skyrl_entrypoint pid=294281) recompute_method: uniform (skyrl_entrypoint pid=294281) recompute_num_layers: 1 (skyrl_entrypoint pid=294281) empty_cuda_cache: true (skyrl_entrypoint pid=294281) ref: (skyrl_entrypoint pid=294281) model: (skyrl_entrypoint pid=294281) path: ${trainer.policy.model.path} (skyrl_entrypoint pid=294281) sequence_parallel_size: 1 (skyrl_entrypoint pid=294281) deepspeed_config: ${deepspeed_config.eval} (skyrl_entrypoint pid=294281) fsdp_config: (skyrl_entrypoint pid=294281) cpu_offload: false (skyrl_entrypoint pid=294281) reshard_after_forward: true (skyrl_entrypoint pid=294281) fsdp_size: 4 (skyrl_entrypoint pid=294281) expert_model_parallel_size: 1 (skyrl_entrypoint pid=294281) expert_tensor_parallel_size: 1 (skyrl_entrypoint pid=294281) moe_token_dispatcher_type: alltoall (skyrl_entrypoint pid=294281) moe_router_replay: false (skyrl_entrypoint pid=294281) moe_grouped_gemm: false (skyrl_entrypoint pid=294281) ep_comm_backend: torch (skyrl_entrypoint pid=294281) deepep_num_sms: 20 (skyrl_entrypoint pid=294281) deepep_token_chunk_size: null (skyrl_entrypoint pid=294281) megatron_config: (skyrl_entrypoint pid=294281) tensor_model_parallel_size: 1 (skyrl_entrypoint pid=294281) pipeline_model_parallel_size: 1 (skyrl_entrypoint pid=294281) context_parallel_size: 1 (skyrl_entrypoint pid=294281) expert_model_parallel_size: 1 (skyrl_entrypoint pid=294281) expert_tensor_parallel_size: 1 (skyrl_entrypoint pid=294281) model_config_kwargs: {} (skyrl_entrypoint pid=294281) transformer_config_kwargs: {} (skyrl_entrypoint pid=294281) critic: (skyrl_entrypoint pid=294281) model: (skyrl_entrypoint pid=294281) path: null (skyrl_entrypoint pid=294281) lora: (skyrl_entrypoint pid=294281) rank: 0 (skyrl_entrypoint pid=294281) alpha: 16 (skyrl_entrypoint pid=294281) dropout: 0 (skyrl_entrypoint pid=294281) target_modules: all-linear (skyrl_entrypoint pid=294281) exclude_modules: null (skyrl_entrypoint pid=294281) deepspeed_config: ${deepspeed_config.train} (skyrl_entrypoint pid=294281) optimizer_config: (skyrl_entrypoint pid=294281) optimizer: AdamW (skyrl_entrypoint pid=294281) lr: 5.0e-06 (skyrl_entrypoint pid=294281) adam_betas: (skyrl_entrypoint pid=294281) - 0.9 (skyrl_entrypoint pid=294281) - 0.999 (skyrl_entrypoint pid=294281) weight_decay: 0.01 (skyrl_entrypoint pid=294281) max_grad_norm: 1.0 (skyrl_entrypoint pid=294281) offload_after_step: true (skyrl_entrypoint pid=294281) num_warmup_steps: 0 (skyrl_entrypoint pid=294281) scheduler: constant_with_warmup (skyrl_entrypoint pid=294281) optimizer_kwargs: {} (skyrl_entrypoint pid=294281) fsdp_config: (skyrl_entrypoint pid=294281) cpu_offload: false (skyrl_entrypoint pid=294281) reshard_after_forward: true (skyrl_entrypoint pid=294281) fsdp_size: -1 (skyrl_entrypoint pid=294281) expert_model_parallel_size: 1 (skyrl_entrypoint pid=294281) expert_tensor_parallel_size: 1 (skyrl_entrypoint pid=294281) moe_token_dispatcher_type: alltoall (skyrl_entrypoint pid=294281) moe_router_replay: false (skyrl_entrypoint pid=294281) moe_grouped_gemm: false (skyrl_entrypoint pid=294281) ep_comm_backend: torch (skyrl_entrypoint pid=294281) deepep_num_sms: 20 (skyrl_entrypoint pid=294281) deepep_token_chunk_size: null (skyrl_entrypoint pid=294281) sequence_parallel_size: 1 (skyrl_entrypoint pid=294281) algorithm: (skyrl_entrypoint pid=294281) advantage_estimator: rloo_n (skyrl_entrypoint pid=294281) kl_ctrl: (skyrl_entrypoint pid=294281) type: fixed (skyrl_entrypoint pid=294281) kl_target: 0.1 (skyrl_entrypoint pid=294281) horizon: 10000 (skyrl_entrypoint pid=294281) kl_estimator_type: k3 (skyrl_entrypoint pid=294281) use_kl_estimator_k3: false (skyrl_entrypoint pid=294281) use_abs_kl: false (skyrl_entrypoint pid=294281) use_kl_in_reward: false (skyrl_entrypoint pid=294281) use_kl_loss: false (skyrl_entrypoint pid=294281) kl_loss_coef: 0.0 (skyrl_entrypoint pid=294281) use_entropy_loss: false (skyrl_entrypoint pid=294281) entropy_loss_coef: 0.01 (skyrl_entrypoint pid=294281) advantage_batch_normalize: false (skyrl_entrypoint pid=294281) value_head_prefix: value_head (skyrl_entrypoint pid=294281) policy_loss_type: regular (skyrl_entrypoint pid=294281) loss_reduction: sequence_mean (skyrl_entrypoint pid=294281) global_loss_denom: null (skyrl_entrypoint pid=294281) grpo_norm_by_std: true (skyrl_entrypoint pid=294281) rloo_n_min_group_size: 4 (skyrl_entrypoint pid=294281) rloo_n_filter_zero_reward_groups: true (skyrl_entrypoint pid=294281) lambd: 1.0 (skyrl_entrypoint pid=294281) gamma: 1.0 (skyrl_entrypoint pid=294281) eps_clip_low: 0.2 (skyrl_entrypoint pid=294281) eps_clip_high: 0.05 (skyrl_entrypoint pid=294281) clip_ratio_c: 3.0 (skyrl_entrypoint pid=294281) tis_imp_ratio_cap: -1.0 (skyrl_entrypoint pid=294281) use_tis: false (skyrl_entrypoint pid=294281) sapo: (skyrl_entrypoint pid=294281) tau_pos: 1.0 (skyrl_entrypoint pid=294281) tau_neg: 1.05 (skyrl_entrypoint pid=294281) value_clip: 0.2 (skyrl_entrypoint pid=294281) dynamic_sampling: (skyrl_entrypoint pid=294281) type: null (skyrl_entrypoint pid=294281) max_sample_batches: 30 (skyrl_entrypoint pid=294281) min_replace_ratio: 0.3 (skyrl_entrypoint pid=294281) clip_cov: (skyrl_entrypoint pid=294281) clip_ratio: 0.0002 (skyrl_entrypoint pid=294281) clip_cov_lb: 1.0 (skyrl_entrypoint pid=294281) clip_cov_ub: 5.0 (skyrl_entrypoint pid=294281) kl_cov: (skyrl_entrypoint pid=294281) kl_cov_frac: 0.2 (skyrl_entrypoint pid=294281) ppo_kl_coef: 1.0 (skyrl_entrypoint pid=294281) cispo: (skyrl_entrypoint pid=294281) cispo_eps_clip_low: 0 (skyrl_entrypoint pid=294281) cispo_eps_clip_high: 5 (skyrl_entrypoint pid=294281) z_clip: (skyrl_entrypoint pid=294281) enabled: false (skyrl_entrypoint pid=294281) alpha: 0.97 (skyrl_entrypoint pid=294281) z_thresh: 2.5 (skyrl_entrypoint pid=294281) warmup_steps: 25 (skyrl_entrypoint pid=294281) mode: zscore (skyrl_entrypoint pid=294281) clip_option: adaptive_scaling (skyrl_entrypoint pid=294281) clip_factor: 1.0 (skyrl_entrypoint pid=294281) skip_update_on_spike: false (skyrl_entrypoint pid=294281) stale_clip: (skyrl_entrypoint pid=294281) enabled: false (skyrl_entrypoint pid=294281) alpha: 0.3 (skyrl_entrypoint pid=294281) entropy_threshold: 0.15 (skyrl_entrypoint pid=294281) entropy_window: 10 (skyrl_entrypoint pid=294281) min_lr_scale: 0.1 (skyrl_entrypoint pid=294281) max_seq_len: 1004095 (skyrl_entrypoint pid=294281) fully_async: (skyrl_entrypoint pid=294281) max_staleness_steps: 16 (skyrl_entrypoint pid=294281) num_parallel_generation_workers: 338 (skyrl_entrypoint pid=294281) gradient_checkpointing: true (skyrl_entrypoint pid=294281) gradient_checkpointing_use_reentrant: false (skyrl_entrypoint pid=294281) seed: 42 (skyrl_entrypoint pid=294281) resume_mode: latest (skyrl_entrypoint pid=294281) resume_path: null (skyrl_entrypoint pid=294281) ckpt_path: /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/checkpoints (skyrl_entrypoint pid=294281) max_ckpts_to_keep: -1 (skyrl_entrypoint pid=294281) ckpt_interval: 2 (skyrl_entrypoint pid=294281) hf_save_interval: 5 (skyrl_entrypoint pid=294281) hf_upload_mode: latest (skyrl_entrypoint pid=294281) export_path: /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/exports (skyrl_entrypoint pid=294281) bf16: true (skyrl_entrypoint pid=294281) epochs: 2 (skyrl_entrypoint pid=294281) max_steps: 80 (skyrl_entrypoint pid=294281) update_epochs_per_batch: 1 (skyrl_entrypoint pid=294281) train_batch_size: 64 (skyrl_entrypoint pid=294281) policy_mini_batch_size: 64 (skyrl_entrypoint pid=294281) critic_mini_batch_size: 256 (skyrl_entrypoint pid=294281) micro_train_batch_size_per_gpu: 1 (skyrl_entrypoint pid=294281) micro_forward_batch_size_per_gpu: 4 (skyrl_entrypoint pid=294281) update_ref_every_epoch: false (skyrl_entrypoint pid=294281) use_sample_packing: true (skyrl_entrypoint pid=294281) eval_batch_size: 64 (skyrl_entrypoint pid=294281) eval_before_train: false (skyrl_entrypoint pid=294281) eval_interval: 999999 (skyrl_entrypoint pid=294281) max_prompt_length: 999999 (skyrl_entrypoint pid=294281) flash_attn: true (skyrl_entrypoint pid=294281) disable_fast_tokenizer: false (skyrl_entrypoint pid=294281) target_modules: null (skyrl_entrypoint pid=294281) exclude_modules: null (skyrl_entrypoint pid=294281) project_name: OpenThoughts-Agent (skyrl_entrypoint pid=294281) run_name: ablation-pymethods2test-seqmean-arm0 (skyrl_entrypoint pid=294281) logger: console (skyrl_entrypoint pid=294281) tracker_commit_each_step: true (skyrl_entrypoint pid=294281) dump_data_batch: false (skyrl_entrypoint pid=294281) dump_eval_results: true (skyrl_entrypoint pid=294281) log_level: INFO (skyrl_entrypoint pid=294281) rope_scaling: null (skyrl_entrypoint pid=294281) rope_theta: null (skyrl_entrypoint pid=294281) step_wise_training: false (skyrl_entrypoint pid=294281) hf_hub_repo_id: laion/ablation-pymethods2test-seqmean-arm0 (skyrl_entrypoint pid=294281) hf_hub_private: false (skyrl_entrypoint pid=294281) hf_hub_revision: main (skyrl_entrypoint pid=294281) enable_db_registration: false (skyrl_entrypoint pid=294281) generator: (skyrl_entrypoint pid=294281) model_name: ${trainer.policy.model.path} (skyrl_entrypoint pid=294281) model_dtype: bfloat16 (skyrl_entrypoint pid=294281) timeout_multiplier: 1.0 (skyrl_entrypoint pid=294281) run_engines_locally: true (skyrl_entrypoint pid=294281) num_inference_engines: 48 (skyrl_entrypoint pid=294281) backend: vllm (skyrl_entrypoint pid=294281) weight_sync_backend: nccl (skyrl_entrypoint pid=294281) fuse_weights: false (skyrl_entrypoint pid=294281) weight_transfer_threshold_cuda_ipc_GB: 1.0 (skyrl_entrypoint pid=294281) inference_engine_tensor_parallel_size: 1 (skyrl_entrypoint pid=294281) inference_engine_pipeline_parallel_size: 1 (skyrl_entrypoint pid=294281) inference_engine_expert_parallel_size: 1 (skyrl_entrypoint pid=294281) inference_engine_data_parallel_size: 1 (skyrl_entrypoint pid=294281) n_samples_per_prompt: 8 (skyrl_entrypoint pid=294281) async_engine: true (skyrl_entrypoint pid=294281) batched: false (skyrl_entrypoint pid=294281) max_input_length: ${trainer.max_prompt_length} (skyrl_entrypoint pid=294281) vllm_v1_disable_multiproc: true (skyrl_entrypoint pid=294281) enable_prefix_caching: true (skyrl_entrypoint pid=294281) enable_chunked_prefill: true (skyrl_entrypoint pid=294281) max_num_batched_tokens: 65536 (skyrl_entrypoint pid=294281) enforce_eager: true (skyrl_entrypoint pid=294281) fully_sharded_loras: false (skyrl_entrypoint pid=294281) enable_ray_prometheus_stats: false (skyrl_entrypoint pid=294281) vllm_stats_interval: 1 (skyrl_entrypoint pid=294281) gpu_memory_utilization: 0.75 (skyrl_entrypoint pid=294281) max_num_seqs: 24 (skyrl_entrypoint pid=294281) remote_inference_engine_urls: (skyrl_entrypoint pid=294281) - 127.0.0.1:8001 (skyrl_entrypoint pid=294281) enable_http_endpoint: true (skyrl_entrypoint pid=294281) http_endpoint_host: 127.0.0.1 (skyrl_entrypoint pid=294281) http_endpoint_port: 8000 (skyrl_entrypoint pid=294281) max_turns: 999999 (skyrl_entrypoint pid=294281) chat_template: (skyrl_entrypoint pid=294281) source: name (skyrl_entrypoint pid=294281) name_or_path: null (skyrl_entrypoint pid=294281) chat_template_kwargs: {} (skyrl_entrypoint pid=294281) engine_init_kwargs: (skyrl_entrypoint pid=294281) max_model_len: 32768 (skyrl_entrypoint pid=294281) custom_chat_template_chat_completion_path: chat_templates/qwen3_thinking_acc.jinja2 (skyrl_entrypoint pid=294281) served_model_name: 0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6 (skyrl_entrypoint pid=294281) override_existing_update_group: disable (skyrl_entrypoint pid=294281) sampling_params: (skyrl_entrypoint pid=294281) max_generate_length: 4096 (skyrl_entrypoint pid=294281) repetition_penalty: 1.0 (skyrl_entrypoint pid=294281) temperature: 0.7 (skyrl_entrypoint pid=294281) top_p: 0.95 (skyrl_entrypoint pid=294281) min_p: 0.0 (skyrl_entrypoint pid=294281) top_k: 20 (skyrl_entrypoint pid=294281) logprobs: null (skyrl_entrypoint pid=294281) stop: null (skyrl_entrypoint pid=294281) use_conversation_multi_turn: true (skyrl_entrypoint pid=294281) append_eos_token_after_stop_str_in_multi_turn: true (skyrl_entrypoint pid=294281) eval_sampling_params: (skyrl_entrypoint pid=294281) max_generate_length: ${generator.sampling_params.max_generate_length} (skyrl_entrypoint pid=294281) repetition_penalty: 1.0 (skyrl_entrypoint pid=294281) temperature: 0.0 (skyrl_entrypoint pid=294281) top_p: 1.0 (skyrl_entrypoint pid=294281) min_p: 0.0 (skyrl_entrypoint pid=294281) top_k: -1 (skyrl_entrypoint pid=294281) logprobs: null (skyrl_entrypoint pid=294281) stop: null (skyrl_entrypoint pid=294281) eval_n_samples_per_prompt: 8 (skyrl_entrypoint pid=294281) zero_reward_on_non_stop: false (skyrl_entrypoint pid=294281) apply_overlong_filtering: false (skyrl_entrypoint pid=294281) rope_scaling: ${trainer.rope_scaling} (skyrl_entrypoint pid=294281) rope_theta: ${trainer.rope_theta} (skyrl_entrypoint pid=294281) teacher: (skyrl_entrypoint pid=294281) model_path: null (skyrl_entrypoint pid=294281) top_k_logprobs: 256 (skyrl_entrypoint pid=294281) num_inference_engines: 1 (skyrl_entrypoint pid=294281) inference_engine_tensor_parallel_size: 1 (skyrl_entrypoint pid=294281) inference_engine_pipeline_parallel_size: 1 (skyrl_entrypoint pid=294281) gpu_memory_utilization: 0.9 (skyrl_entrypoint pid=294281) enforce_eager: false (skyrl_entrypoint pid=294281) backend: vllm (skyrl_entrypoint pid=294281) engine_init_kwargs: {} (skyrl_entrypoint pid=294281) environment: (skyrl_entrypoint pid=294281) env_class: gsm8k (skyrl_entrypoint pid=294281) skyrl_gym: (skyrl_entrypoint pid=294281) max_env_workers: 32 (skyrl_entrypoint pid=294281) text2sql: (skyrl_entrypoint pid=294281) db_path: /home/ray/default/sql_data (skyrl_entrypoint pid=294281) llm_as_a_judge: (skyrl_entrypoint pid=294281) model: gpt-4o-mini (skyrl_entrypoint pid=294281) base_url: null (skyrl_entrypoint pid=294281) search: (skyrl_entrypoint pid=294281) log_requests: false (skyrl_entrypoint pid=294281) search_url: http://127.0.0.1:8000/retrieve (skyrl_entrypoint pid=294281) topk: 3 (skyrl_entrypoint pid=294281) timeout: 30 (skyrl_entrypoint pid=294281) rollout: (skyrl_entrypoint pid=294281) fanout: (skyrl_entrypoint pid=294281) enabled: true (skyrl_entrypoint pid=294281) num_coordinators: 4 (skyrl_entrypoint pid=294281) cpus_per_coordinator: 8 (skyrl_entrypoint pid=294281) deepspeed_config: (skyrl_entrypoint pid=294281) train: (skyrl_entrypoint pid=294281) zero_optimization: (skyrl_entrypoint pid=294281) stage: 3 (skyrl_entrypoint pid=294281) offload_param: (skyrl_entrypoint pid=294281) device: none (skyrl_entrypoint pid=294281) offload_optimizer: (skyrl_entrypoint pid=294281) device: none (skyrl_entrypoint pid=294281) pin_memory: true (skyrl_entrypoint pid=294281) sub_group_size: auto (skyrl_entrypoint pid=294281) reduce_bucket_size: auto (skyrl_entrypoint pid=294281) stage3_param_persistence_threshold: auto (skyrl_entrypoint pid=294281) stage3_prefetch_bucket_size: auto (skyrl_entrypoint pid=294281) stage3_max_live_parameters: auto (skyrl_entrypoint pid=294281) stage3_max_reuse_distance: auto (skyrl_entrypoint pid=294281) round_robin_gradients: true (skyrl_entrypoint pid=294281) zero_hpz_partition_size: 1 (skyrl_entrypoint pid=294281) zero_quantized_weights: false (skyrl_entrypoint pid=294281) zero_quantized_gradients: false (skyrl_entrypoint pid=294281) torch_autocast: (skyrl_entrypoint pid=294281) enabled: true (skyrl_entrypoint pid=294281) dtype: bfloat16 (skyrl_entrypoint pid=294281) disable_trace_cache: false (skyrl_entrypoint pid=294281) data_types: (skyrl_entrypoint pid=294281) grad_accum_dtype: fp32 (skyrl_entrypoint pid=294281) gradient_clipping: 1.0 (skyrl_entrypoint pid=294281) wall_clock_breakdown: false (skyrl_entrypoint pid=294281) prescale_gradient: false (skyrl_entrypoint pid=294281) eval: (skyrl_entrypoint pid=294281) zero_optimization: (skyrl_entrypoint pid=294281) stage: 3 (skyrl_entrypoint pid=294281) stage3_param_persistence_threshold: auto (skyrl_entrypoint pid=294281) offload_param: (skyrl_entrypoint pid=294281) device: cpu (skyrl_entrypoint pid=294281) pin_memory: true (skyrl_entrypoint pid=294281) torch_autocast: (skyrl_entrypoint pid=294281) enabled: true (skyrl_entrypoint pid=294281) dtype: bfloat16 (skyrl_entrypoint pid=294281) gradient_clipping: 1.0 (skyrl_entrypoint pid=294281) prescale_gradient: false (skyrl_entrypoint pid=294281) wall_clock_breakdown: false (skyrl_entrypoint pid=294281) terminal_bench_config: (skyrl_entrypoint pid=294281) trials_dir: /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/trace_jobs (skyrl_entrypoint pid=294281) harbor: (skyrl_entrypoint pid=294281) name: terminus-2 (skyrl_entrypoint pid=294281) max_episodes: 999999 (skyrl_entrypoint pid=294281) enable_summarize: false (skyrl_entrypoint pid=294281) store_all_messages: true (skyrl_entrypoint pid=294281) trajectory_config: (skyrl_entrypoint pid=294281) raw_content: true (skyrl_entrypoint pid=294281) enable_episode_logging: false (skyrl_entrypoint pid=294281) record_terminal_session: false (skyrl_entrypoint pid=294281) enable_pane_logging: false (skyrl_entrypoint pid=294281) strict_json_parser: true (skyrl_entrypoint pid=294281) interleaved_thinking: true (skyrl_entrypoint pid=294281) extra_body: (skyrl_entrypoint pid=294281) chat_template_kwargs: (skyrl_entrypoint pid=294281) enable_thinking: true (skyrl_entrypoint pid=294281) override_timeout_sec: 900 (skyrl_entrypoint pid=294281) override_cpus: 1 (skyrl_entrypoint pid=294281) override_memory_mb: 2048 (skyrl_entrypoint pid=294281) override_storage_mb: 2048 (skyrl_entrypoint pid=294281) auto_snapshot: true (skyrl_entrypoint pid=294281) verifier_override_timeout_sec: 120 (skyrl_entrypoint pid=294281) max_retries: 3 (skyrl_entrypoint pid=294281) min_wait_sec: 60.0 (skyrl_entrypoint pid=294281) max_wait_sec: 600.0 (skyrl_entrypoint pid=294281) wait_multiplier: 2.0 (skyrl_entrypoint pid=294281) exclude_exceptions: (skyrl_entrypoint pid=294281) - VerifierTimeoutError (skyrl_entrypoint pid=294281) - VerifierRuntimeError (skyrl_entrypoint pid=294281) - RewardFileNotFoundError (skyrl_entrypoint pid=294281) - RewardFileEmptyError (skyrl_entrypoint pid=294281) - VerifierOutputParseError (skyrl_entrypoint pid=294281) n_concurrent_trials: 675 (skyrl_entrypoint pid=294281) log_level: INFO (skyrl_entrypoint pid=294281) enable_reward_shaping: false (skyrl_entrypoint pid=294281) enable_error_classification: true (skyrl_entrypoint pid=294281) mask_exceptions: (skyrl_entrypoint pid=294281) - DaytonaError (skyrl_entrypoint pid=294281) - EnvironmentStartTimeoutError (skyrl_entrypoint pid=294281) - NetworkError (skyrl_entrypoint pid=294281) - ConnectionError (skyrl_entrypoint pid=294281) - RewardFileNotFoundError (skyrl_entrypoint pid=294281) - RewardFileEmptyError (skyrl_entrypoint pid=294281) - AgentEnvironmentTimeoutError (skyrl_entrypoint pid=294281) - ContextLengthExceededError (skyrl_entrypoint pid=294281) default_error_treatment: zero (skyrl_entrypoint pid=294281) passthrough_exceptions: (skyrl_entrypoint pid=294281) - AgentTimeoutError (skyrl_entrypoint pid=294281) zero_exceptions: [] (skyrl_entrypoint pid=294281) model_info: (skyrl_entrypoint pid=294281) max_input_tokens: 32000 (skyrl_entrypoint pid=294281) max_output_tokens: 4096 (skyrl_entrypoint pid=294281) archiving: (skyrl_entrypoint pid=294281) enabled: false (skyrl_entrypoint pid=294281) trace_upload: (skyrl_entrypoint pid=294281) enabled: true (skyrl_entrypoint pid=294281) repo_org: DCAgent (skyrl_entrypoint pid=294281) episodes: last (skyrl_entrypoint pid=294281) dataset_type: SFT (skyrl_entrypoint pid=294281) cleanup: true (skyrl_entrypoint pid=294281)  (skyrl_entrypoint pid=294281) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: (skyrl_entrypoint pid=294281) No module named 'vllm._version' (skyrl_entrypoint pid=294281) from .version import __version__, __version_tuple__ # isort:skip (skyrl_entrypoint pid=294281) W0607 02:21:22.569000 294281 envs/rl/lib/python3.12/site-packages/torch/utils/cpp_extension.py:117] No CUDA runtime is found, using CUDA_HOME='/e/software/default/stages/2026/software/CUDA/13' [2026-06-07 02:21:23,669 E 293833 294255] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 (RegistryActor pid=987007, ip=10.128.32.37) [2026-06-07 02:21:24,551 E 987007 987047] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 (raylet) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e (skyrl_entrypoint pid=294281) [2026-06-07 02:21:27,013 E 294281 294324] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 [repeated 2x across cluster] (pid=987079, ip=10.128.32.37) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: (pid=987079, ip=10.128.32.37) No module named 'vllm._version' (pid=987079, ip=10.128.32.37) from .version import __version__, __version_tuple__ # isort:skip (raylet, ip=10.128.32.40) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 41x across cluster] (pid=2596339, ip=10.128.32.36) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: [repeated 7x across cluster] (pid=2596339, ip=10.128.32.36) No module named 'vllm._version' [repeated 7x across cluster] (pid=2596339, ip=10.128.32.36) from .version import __version__, __version_tuple__ # isort:skip [repeated 7x across cluster] (raylet, ip=10.128.32.42) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 111x across cluster] (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) 2026-06-07 02:21:40.638 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:123 - setup_envvars_for_vllm: distributed_executor_backend=uni, SKYRL_ENABLE_NUMA_AFFINITY=1, CUDA_VISIBLE_DEVICES=0, VLLM_ENABLE_V1_MULTIPROCESSING= (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) 2026-06-07 02:21:40.638 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:133 - setup_envvars_for_vllm: numa_enabled=True (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) 2026-06-07 02:21:40.639 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:136 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) 2026-06-07 02:21:41.259 | INFO | skyrl_train.utils.numa:set_numa_affinity_for_gpu:340 - NUMA affinity: bound process to CPUs 0-71 (NUMA node 0) for GPU 0 (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) 2026-06-07 02:21:41.284 | DEBUG | skyrl_train.utils.numa:_set_membind_via_libnuma:375 - NUMA affinity: set memory preferred to NUMA node 0 (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) 2026-06-07 02:21:41.284 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:584 - BaseVLLMInferenceEngine: vllm_v1_disable_multiproc=True, vllm.__version__=dev, VLLM_ENABLE_V1_MULTIPROCESSING=0 (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) 2026-06-07 02:21:41.285 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:592 - BaseVLLMInferenceEngine: set VLLM_ENABLE_V1_MULTIPROCESSING=0 (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) 2026-06-07 02:21:41.285 | WARNING | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1158 - OpenAI API sampling params overridden: temperature=0.7, top_p=0.95, top_k=20 (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) 2026-06-07 02:21:41.305 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1210 - Engine startup stagger: sleeping 2.18s (attempt 1/5) to avoid port collisions (pid=2704166, ip=10.128.32.34) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: [repeated 13x across cluster] (pid=2704166, ip=10.128.32.34) No module named 'vllm._version' [repeated 13x across cluster] (pid=2704166, ip=10.128.32.34) from .version import __version__, __version_tuple__ # isort:skip [repeated 13x across cluster] (raylet, ip=10.128.32.46) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 69x across cluster] (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) The tokenizer you are loading from '/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) 2026-06-07 02:21:45.976 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:123 - setup_envvars_for_vllm: distributed_executor_backend=uni, SKYRL_ENABLE_NUMA_AFFINITY=1, CUDA_VISIBLE_DEVICES=1, VLLM_ENABLE_V1_MULTIPROCESSING= (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) 2026-06-07 02:21:45.976 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:133 - setup_envvars_for_vllm: numa_enabled=True (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) 2026-06-07 02:21:45.976 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:136 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity (AsyncVLLMInferenceEngine pid=987214, ip=10.128.32.37) 2026-06-07 02:21:46.027 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:123 - setup_envvars_for_vllm: distributed_executor_backend=uni, SKYRL_ENABLE_NUMA_AFFINITY=1, CUDA_VISIBLE_DEVICES=3, VLLM_ENABLE_V1_MULTIPROCESSING= (AsyncVLLMInferenceEngine pid=987214, ip=10.128.32.37) 2026-06-07 02:21:46.028 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:133 - setup_envvars_for_vllm: numa_enabled=True (AsyncVLLMInferenceEngine pid=987214, ip=10.128.32.37) 2026-06-07 02:21:46.028 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:136 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) 2026-06-07 02:21:46.972 | INFO | skyrl_train.utils.numa:set_numa_affinity_for_gpu:340 - NUMA affinity: bound process to CPUs 72-143 (NUMA node 1) for GPU 1 (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) 2026-06-07 02:21:46.976 | DEBUG | skyrl_train.utils.numa:_set_membind_via_libnuma:375 - NUMA affinity: set memory preferred to NUMA node 1 (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) 2026-06-07 02:21:46.976 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:584 - BaseVLLMInferenceEngine: vllm_v1_disable_multiproc=True, vllm.__version__=dev, VLLM_ENABLE_V1_MULTIPROCESSING=0 (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) 2026-06-07 02:21:46.976 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:592 - BaseVLLMInferenceEngine: set VLLM_ENABLE_V1_MULTIPROCESSING=0 (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) 2026-06-07 02:21:46.976 | WARNING | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1158 - OpenAI API sampling params overridden: temperature=0.7, top_p=0.95, top_k=20 (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) 2026-06-07 02:21:47.003 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1210 - Engine startup stagger: sleeping 1.81s (attempt 1/5) to avoid port collisions (pid=2958820, ip=10.128.32.39) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: [repeated 10x across cluster] (pid=2958820, ip=10.128.32.39) No module named 'vllm._version' [repeated 10x across cluster] (pid=2958820, ip=10.128.32.39) from .version import __version__, __version_tuple__ # isort:skip [repeated 10x across cluster] (raylet, ip=10.128.32.45) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 63x across cluster] (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. [repeated 2x across cluster] (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) The tokenizer you are loading from '/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. (skyrl_entrypoint pid=294281) [2026-06-07 02:21:50] INFO inference_engine_client_http_endpoint.py:350: Starting server on 0.0.0.0:8000 (skyrl_entrypoint pid=294281) [2026-06-07 02:21:50] INFO inference_engine_client_http_endpoint.py:242: Starting inference HTTP endpoint... (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) 2026-06-07 02:21:50.121 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:123 - setup_envvars_for_vllm: distributed_executor_backend=uni, SKYRL_ENABLE_NUMA_AFFINITY=1, CUDA_VISIBLE_DEVICES=3, VLLM_ENABLE_V1_MULTIPROCESSING= [repeated 17x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) 2026-06-07 02:21:50.122 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:133 - setup_envvars_for_vllm: numa_enabled=True [repeated 17x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) 2026-06-07 02:21:50.122 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:136 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity [repeated 17x across cluster] (skyrl_entrypoint pid=294281) [2026-06-07 02:21:51] INFO inference_engine_client_http_endpoint.py:229: Server ready after 2 attempts (2 seconds) (skyrl_entrypoint pid=294281) 2026-06-07 02:21:51.391 | INFO  | skyrl_train.inference_engines.inference_engine_client:_spin_up_http_endpoint:969 - InferenceEngineClient HTTP endpoint started on 127.0.0.1:8000 (skyrl_entrypoint pid=294281) 2026-06-07 02:21:51.391 | INFO  | skyrl_train.inference_engines.inference_engine_client:__init__:61 - InferenceEngineClient initialized with 48 engines. (skyrl_entrypoint pid=294281) 2026-06-07 02:21:51.394 | INFO  | examples.terminal_bench.terminal_bench_generator:_configure_harbor_logging:236 - Harbor logging level set to INFO (skyrl_entrypoint pid=294281) 2026-06-07 02:21:51.395 | INFO  | examples.terminal_bench.terminal_bench_generator:__init__:136 - TerminalBenchGenerator initialized with HarborConfigBuilder. Exposed fields: ['name', 'max_episodes', 'enable_summarize', 'store_all_messages', 'trajectory_config', 'enable_episode_logging', 'record_terminal_session', 'enable_pane_logging', 'strict_json_parser', 'interleaved_thinking', 'extra_body', 'override_timeout_sec', 'override_cpus', 'override_memory_mb', 'override_storage_mb', 'auto_snapshot', 'verifier_override_timeout_sec', 'max_retries', 'min_wait_sec', 'max_wait_sec', 'wait_multiplier', 'exclude_exceptions', 'n_concurrent_trials', 'log_level', 'enable_reward_shaping', 'enable_error_classification', 'mask_exceptions', 'default_error_treatment', 'passthrough_exceptions', 'zero_exceptions']. Retry config: max_retries=3, backoff=60.0-600.0s. Concurrent trials: 675. Reward shaping: enabled=False, shaper=pass_ratio. Error classification: enabled=True (skyrl_entrypoint pid=294281) 2026-06-07 02:21:51.408 | INFO  | examples.terminal_bench.terminal_bench_generator:__init__:152 - TerminalBenchGenerator initialized with custom chat template read from: chat_templates/qwen3_thinking_acc.jinja2 (skyrl_entrypoint pid=294281) 2026-06-07 02:21:51.409 | INFO  | skyrl_train.utils.trainer_utils:build_dataloader:656 - Total steps: 156 (skyrl_entrypoint pid=294281) 2026-06-07 02:21:51.409 | INFO  | skyrl_train.fully_async_trainer:_build_train_dataloader_and_compute_training_steps:357 - Length of train_dataloader: 5000 (skyrl_entrypoint pid=294281) 2026-06-07 02:21:51.409 | INFO  | skyrl_train.fully_async_trainer:_build_train_dataloader_and_compute_training_steps:358 - Number of steps per epoch: 78 (skyrl_entrypoint pid=294281) 2026-06-07 02:21:51.409 | INFO  | skyrl_train.fully_async_trainer:_build_train_dataloader_and_compute_training_steps:359 - Total training steps: 80 (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) 2026-06-07 02:21:51.407 | INFO | skyrl_train.utils.numa:set_numa_affinity_for_gpu:340 - NUMA affinity: bound process to CPUs 216-287 (NUMA node 3) for GPU 3 [repeated 18x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) 2026-06-07 02:21:51.427 | DEBUG | skyrl_train.utils.numa:_set_membind_via_libnuma:375 - NUMA affinity: set memory preferred to NUMA node 3 [repeated 18x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) 2026-06-07 02:21:51.427 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:584 - BaseVLLMInferenceEngine: vllm_v1_disable_multiproc=True, vllm.__version__=dev, VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 18x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) 2026-06-07 02:21:51.427 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:592 - BaseVLLMInferenceEngine: set VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 18x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) 2026-06-07 02:21:51.427 | WARNING | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1158 - OpenAI API sampling params overridden: temperature=0.7, top_p=0.95, top_k=20 [repeated 18x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) 2026-06-07 02:21:51.452 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1210 - Engine startup stagger: sleeping 2.18s (attempt 1/5) to avoid port collisions [repeated 18x across cluster] (AsyncVLLMInferenceEngine pid=2669422, ip=10.128.32.38) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: [repeated 33x across cluster] (AsyncVLLMInferenceEngine pid=2669422, ip=10.128.32.38) No module named 'vllm._version' [repeated 33x across cluster] (AsyncVLLMInferenceEngine pid=2669422, ip=10.128.32.38) from .version import __version__, __version_tuple__ # isort:skip [repeated 33x across cluster] (AsyncVLLMInferenceEngine pid=2669422, ip=10.128.32.38) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 120x across cluster] (AsyncVLLMInferenceEngine pid=3079062, ip=10.128.32.42) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. [repeated 32x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) The tokenizer you are loading from '/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 17x across cluster] (pid=2662729, ip=10.128.32.43) Using blocking ray.get inside async actor. This blocks the event loop. Please use `await` on object ref with asyncio.gather if you want to yield execution to the event loop instead. (AsyncVLLMInferenceEngine pid=2626656, ip=10.128.32.46) 2026-06-07 02:21:55.378 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:123 - setup_envvars_for_vllm: distributed_executor_backend=uni, SKYRL_ENABLE_NUMA_AFFINITY=1, CUDA_VISIBLE_DEVICES=1, VLLM_ENABLE_V1_MULTIPROCESSING= [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2626656, ip=10.128.32.46) 2026-06-07 02:21:55.380 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:133 - setup_envvars_for_vllm: numa_enabled=True [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2626656, ip=10.128.32.46) 2026-06-07 02:21:55.380 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:136 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/__init__.py:1617: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.) (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) [W607 02:21:56.447607181 socket.cpp:767] [c10d] The client socket cannot be initialized to connect to [jpbo-041-37.jupiter.internal]:41139 (errno: 97 - Address family not supported by protocol). (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) [W607 02:21:56.449335629 Utils.hpp:166] Warning: Environment variable NCCL_BLOCKING_WAIT is deprecated; use TORCH_NCCL_BLOCKING_WAIT instead (function operator()) (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) [rank0]:[W607 02:21:56.451880032 Utils.hpp:137] Warning: Environment variable TORCH_NCCL_TRACE_BUFFER_SIZE is deprecated; use TORCH_FR_BUFFER_SIZE instead (function operator()) (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) 2026-06-07 02:21:56.650 | INFO | skyrl_train.utils.numa:set_numa_affinity_for_gpu:340 - NUMA affinity: bound process to CPUs 216-287 (NUMA node 3) for GPU 3 [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) 2026-06-07 02:21:56.652 | DEBUG | skyrl_train.utils.numa:_set_membind_via_libnuma:375 - NUMA affinity: set memory preferred to NUMA node 3 [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) 2026-06-07 02:21:56.652 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:584 - BaseVLLMInferenceEngine: vllm_v1_disable_multiproc=True, vllm.__version__=dev, VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) 2026-06-07 02:21:56.652 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:592 - BaseVLLMInferenceEngine: set VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) 2026-06-07 02:21:56.652 | WARNING | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1158 - OpenAI API sampling params overridden: temperature=0.7, top_p=0.95, top_k=20 [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) 2026-06-07 02:21:56.667 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1210 - Engine startup stagger: sleeping 2.60s (attempt 1/5) to avoid port collisions [repeated 9x across cluster] (bundle_reservation_check_func pid=294359) [2026-06-07 02:21:57,860 E 294359 294399] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 (AsyncVLLMInferenceEngine pid=2704166, ip=10.128.32.34) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2704166, ip=10.128.32.34) No module named 'vllm._version' [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2704166, ip=10.128.32.34) from .version import __version__, __version_tuple__ # isort:skip [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2704294, ip=10.128.32.34) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 18x across cluster] (AsyncVLLMInferenceEngine pid=2626657, ip=10.128.32.46) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. [repeated 18x across cluster] (AsyncVLLMInferenceEngine pid=2626657, ip=10.128.32.46) The tokenizer you are loading from '/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 [repeated 12x across cluster] (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) 2026-06-07 02:21:58.939 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:133 - setup_envvars_for_vllm: numa_enabled=True [repeated 12x across cluster] (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) 2026-06-07 02:21:58.939 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:136 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity [repeated 12x across cluster] (AsyncVLLMInferenceEngine pid=2541854, ip=10.128.32.40) (EngineCore_DP0 pid=2542230) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=2541854, ip=10.128.32.40) (EngineCore_DP0 pid=2542230) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/__init__.py:1617: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.) [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) (EngineCore_DP0 pid=987452) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) [W607 02:22:01.433309818 socket.cpp:767] [c10d] The client socket cannot be initialized to connect to [jpbo-041-37.jupiter.internal]:50831 (errno: 97 - Address family not supported by protocol). [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) [W607 02:22:01.433831729 Utils.hpp:166] Warning: Environment variable NCCL_BLOCKING_WAIT is deprecated; use TORCH_NCCL_BLOCKING_WAIT instead (function operator()) [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) [rank0]:[W607 02:22:01.436403587 Utils.hpp:137] Warning: Environment variable TORCH_NCCL_TRACE_BUFFER_SIZE is deprecated; use TORCH_FR_BUFFER_SIZE instead (function operator()) [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) Loading safetensors checkpoint shards: 25% Completed | 1/4 [00:02<00:08, 2.86s/it] (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) 2026-06-07 02:22:00.236 | INFO | skyrl_train.utils.numa:set_numa_affinity_for_gpu:340 - NUMA affinity: bound process to CPUs 216-287 (NUMA node 3) for GPU 3 [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) 2026-06-07 02:22:00.261 | DEBUG | skyrl_train.utils.numa:_set_membind_via_libnuma:375 - NUMA affinity: set memory preferred to NUMA node 3 [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) 2026-06-07 02:22:00.261 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:584 - BaseVLLMInferenceEngine: vllm_v1_disable_multiproc=True, vllm.__version__=dev, VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) 2026-06-07 02:22:00.261 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:592 - BaseVLLMInferenceEngine: set VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) 2026-06-07 02:22:00.261 | WARNING | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1158 - OpenAI API sampling params overridden: temperature=0.7, top_p=0.95, top_k=20 [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) 2026-06-07 02:22:00.294 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1210 - Engine startup stagger: sleeping 1.55s (attempt 1/5) to avoid port collisions [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=2542123, ip=10.128.32.40) (EngineCore_DP0 pid=2542234) _C._set_float32_matmul_precision(precision) (pid=2662807, ip=10.128.32.43) Using blocking ray.get inside async actor. This blocks the event loop. Please use `await` on object ref with asyncio.gather if you want to yield execution to the event loop instead. (AsyncVLLMInferenceEngine pid=2541854, ip=10.128.32.40) [2026-06-07 02:22:01,958 E 2541854 2541963] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 [repeated 6x across cluster] (AsyncVLLMInferenceEngine pid=2541994, ip=10.128.32.40) (EngineCore_DP0 pid=2542240) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: [repeated 15x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) No module named 'vllm._version' [repeated 15x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) from .version import __version__, __version_tuple__ # isort:skip [repeated 15x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 72x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. [repeated 26x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) The tokenizer you are loading from '/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 13x across cluster] (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) (EngineCore_DP0 pid=987452) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) 2026-06-07 02:22:01.691 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:133 - setup_envvars_for_vllm: numa_enabled=True [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) 2026-06-07 02:22:01.691 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:136 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2596338, ip=10.128.32.36) (EngineCore_DP0 pid=2596579) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=3079063, ip=10.128.32.42) (EngineCore_DP0 pid=3079292) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=3079063, ip=10.128.32.42) (EngineCore_DP0 pid=3079292) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/__init__.py:1617: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.) [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2596340, ip=10.128.32.36) (EngineCore_DP0 pid=2596570) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=2596340, ip=10.128.32.36) [W607 02:22:06.608280396 socket.cpp:767] [c10d] The client socket cannot be initialized to connect to [jpbo-041-36.jupiter.internal]:36675 (errno: 97 - Address family not supported by protocol). [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2596340, ip=10.128.32.36) [W607 02:22:06.608742019 Utils.hpp:166] Warning: Environment variable NCCL_BLOCKING_WAIT is deprecated; use TORCH_NCCL_BLOCKING_WAIT instead (function operator()) [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2596340, ip=10.128.32.36) [rank0]:[W607 02:22:06.611067956 Utils.hpp:137] Warning: Environment variable TORCH_NCCL_TRACE_BUFFER_SIZE is deprecated; use TORCH_FR_BUFFER_SIZE instead (function operator()) [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) Loading safetensors checkpoint shards: 75% Completed | 3/4 [00:07<00:02, 2.64s/it] [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2669551, ip=10.128.32.38) (EngineCore_DP0 pid=2669786) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=2669422, ip=10.128.32.38) (EngineCore_DP0 pid=2669802) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) 2026-06-07 02:22:02.951 | INFO | skyrl_train.utils.numa:set_numa_affinity_for_gpu:340 - NUMA affinity: bound process to CPUs 72-143 (NUMA node 1) for GPU 1 [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) 2026-06-07 02:22:02.975 | DEBUG | skyrl_train.utils.numa:_set_membind_via_libnuma:375 - NUMA affinity: set memory preferred to NUMA node 1 [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) 2026-06-07 02:22:02.975 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:584 - BaseVLLMInferenceEngine: vllm_v1_disable_multiproc=True, vllm.__version__=dev, VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) 2026-06-07 02:22:02.975 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:592 - BaseVLLMInferenceEngine: set VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) 2026-06-07 02:22:02.976 | WARNING | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1158 - OpenAI API sampling params overridden: temperature=0.7, top_p=0.95, top_k=20 [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) 2026-06-07 02:22:03.008 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1210 - Engine startup stagger: sleeping 2.80s (attempt 1/5) to avoid port collisions [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=3078934, ip=10.128.32.42) (EngineCore_DP0 pid=3079317) _C._set_float32_matmul_precision(precision) (pid=294462) Using blocking ray.get inside async actor. This blocks the event loop. Please use `await` on object ref with asyncio.gather if you want to yield execution to the event loop instead. [repeated 6x across cluster] (AsyncVLLMInferenceEngine pid=2669552, ip=10.128.32.38) (EngineCore_DP0 pid=2669784) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=2669552, ip=10.128.32.38) [2026-06-07 02:22:07,570 E 2669552 2669716] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 [repeated 18x across cluster] (AsyncVLLMInferenceEngine pid=3079062, ip=10.128.32.42) (EngineCore_DP0 pid=3079296) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) (EngineCore_DP0 pid=987452) (AsyncVLLMInferenceEngine pid=987214, ip=10.128.32.37) (EngineCore_DP0 pid=987460) (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) (EngineCore_DP0 pid=987447) (AsyncVLLMInferenceEngine pid=2669550, ip=10.128.32.38) (EngineCore_DP0 pid=2669785) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) No module named 'vllm._version' [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) from .version import __version__, __version_tuple__ # isort:skip [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) The tokenizer you are loading from '/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2669422, ip=10.128.32.38) (EngineCore_DP0 pid=2669802) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) 2026-06-07 02:22:13.432 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:133 - setup_envvars_for_vllm: numa_enabled=True (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) 2026-06-07 02:22:13.432 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:136 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) (EngineCore_DP0 pid=2975787) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=2626657, ip=10.128.32.46) (EngineCore_DP0 pid=2626889) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) (EngineCore_DP0 pid=987447) The tokenizer you are loading from '/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2958819, ip=10.128.32.39) (EngineCore_DP0 pid=2959046) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) 2026-06-07 02:22:14.790 | INFO | skyrl_train.utils.numa:set_numa_affinity_for_gpu:340 - NUMA affinity: bound process to CPUs 0-71 (NUMA node 0) for GPU 0 (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) 2026-06-07 02:22:14.816 | DEBUG | skyrl_train.utils.numa:_set_membind_via_libnuma:375 - NUMA affinity: set memory preferred to NUMA node 0 (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) 2026-06-07 02:22:14.816 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:584 - BaseVLLMInferenceEngine: vllm_v1_disable_multiproc=True, vllm.__version__=dev, VLLM_ENABLE_V1_MULTIPROCESSING=0 (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) 2026-06-07 02:22:14.817 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:592 - BaseVLLMInferenceEngine: set VLLM_ENABLE_V1_MULTIPROCESSING=0 (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) 2026-06-07 02:22:14.817 | WARNING | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1158 - OpenAI API sampling params overridden: temperature=0.7, top_p=0.95, top_k=20 (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) 2026-06-07 02:22:14.850 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1210 - Engine startup stagger: sleeping 1.65s (attempt 1/5) to avoid port collisions (AsyncVLLMInferenceEngine pid=2975429, ip=10.128.32.44) (EngineCore_DP0 pid=2975795) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=2704295, ip=10.128.32.34) (EngineCore_DP0 pid=2704527) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00, std::allocator >) + 0xb0 (0x40006f4ac700 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libc10.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #1: + 0x5f29220 (0x40004f649220 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #2: + 0x5f4326c (0x40004f66326c in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #3: + 0x5f49074 (0x40004f669074 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #4: + 0x5f49138 (0x40004f669138 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #5: + 0x5f2ccc4 (0x40004f64ccc4 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #6: c10d::TCPStore::TCPStore(std::__cxx11::basic_string, std::allocator >, c10d::TCPStoreOptions const&) + 0x104 (0x40004f651564 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #7: + 0x109a094 (0x4000493fa094 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_python.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #8: + 0x113236c (0x40004949236c in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_python.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #9: + 0x5d6d60 (0x400048936d60 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_python.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #10: + 0x1b7a38 (0xaaaab8697a38 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #11: _PyObject_MakeTpCall + 0x98 (0xaaaab8645db8 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #12: + 0x169f50 (0xaaaab8649f50 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #13: + 0x1682e4 (0xaaaab86482e4 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #14: + 0x1e0ce8 (0xaaaab86c0ce8 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #15: + 0x1d7ddc (0xaaaab86b7ddc in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #16: + 0x646b0c (0x4000489a6b0c in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_python.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #17: _PyObject_MakeTpCall + 0x98 (0xaaaab8645db8 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #18: _PyEval_EvalFrameDefault + 0x280c (0xaaaab874ae54 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #19: + 0x1808c0 (0xaaaab86608c0 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #20: + 0x182bf8 (0xaaaab8662bf8 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #21: + 0x25fd30 (0xaaaab873fd30 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #22: + 0x1b7d20 (0xaaaab8697d20 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #23: PyObject_Vectorcall + 0x54 (0xaaaab86460e4 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #24: _PyEval_EvalFrameDefault + 0x280c (0xaaaab874ae54 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #25: _PyObject_FastCallDictTstate + 0x80 (0xaaaab8647f20 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #26: _PyObject_Call_Prepend + 0x140 (0xaaaab86481ec in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #27: + 0x1e0d80 (0xaaaab86c0d80 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #28: + 0x1d7ddc (0xaaaab86b7ddc in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #29: _PyObject_MakeTpCall + 0x98 (0xaaaab8645db8 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #30: _PyEval_EvalFrameDefault + 0x280c (0xaaaab874ae54 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #31: _PyObject_FastCallDictTstate + 0x10c (0xaaaab8647fac in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #32: _PyObject_Call_Prepend + 0x140 (0xaaaab86481ec in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #33: + 0x1e0d80 (0xaaaab86c0d80 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #34: + 0x1d7ddc (0xaaaab86b7ddc in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #35: _PyObject_Call + 0x68 (0xaaaab8648488 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #36: _PyEval_EvalFrameDefault + 0x52ac (0xaaaab874d8f4 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #37: PyEval_EvalCode + 0xb4 (0xaaaab8752eb4 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #38: + 0x2ccdcc (0xaaaab87acdcc in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #39: + 0x2ccef4 (0xaaaab87acef4 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #40: PyRun_StringFlags + 0x90 (0xaaaab87b1050 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #41: PyRun_SimpleStringFlags + 0x58 (0xaaaab87b10f8 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #42: Py_RunMain + 0x2c8 (0xaaaab87d9190 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #43: Py_BytesMain + 0x64 (0xaaaab87d9fb4 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #44: + 0x27540 (0x4000379a7540 in /lib64/libc.so.6) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #45: __libc_start_main + 0x98 (0x4000379a7618 in /lib64/libc.so.6) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) frame #46: + 0x10e0c0 (0xaaaab85ee0c0 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) [pynccl] dumped 0 entries to /e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps/nccl_trace_pynccl_pid2959070 (reason=atexit) (AsyncVLLMInferenceEngine pid=2975564, ip=10.128.32.44) (EngineCore_DP0 pid=2975800) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) (EngineCore_DP0 pid=2975804) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=2796150, ip=10.128.32.45) (EngineCore_DP0 pid=2796384) (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored. (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) (EngineCore_DP0 pid=2975804) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/__init__.py:1617: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.) [repeated 18x across cluster] (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) [W607 02:22:16.342198091 socket.cpp:767] [c10d] The client socket cannot be initialized to connect to [jpbo-041-44.jupiter.internal]:41207 (errno: 97 - Address family not supported by protocol). [repeated 17x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) [W607 02:22:16.342706915 Utils.hpp:166] Warning: Environment variable NCCL_BLOCKING_WAIT is deprecated; use TORCH_NCCL_BLOCKING_WAIT instead (function operator()) [repeated 17x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) [rank0]:[W607 02:22:16.344851394 Utils.hpp:137] Warning: Environment variable TORCH_NCCL_TRACE_BUFFER_SIZE is deprecated; use TORCH_FR_BUFFER_SIZE instead (function operator()) [repeated 17x across cluster] (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) Exception raised in creation task: The actor died because of an error raised in its creation task, ray::AsyncVLLMInferenceEngine.__init__() (pid=2958691, ip=10.128.32.39, actor_id=9f591a871969d2b79a9e310202000000, repr=) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/concurrent/futures/_base.py", line 449, in result (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) return self.__get_result() (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) ^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) raise self._exception (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) ^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 1139, in __init__ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) super().__init__(*args, **kwargs) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 603, in __init__ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) self.llm = self._create_engine(*args, **kwargs) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 1216, in _create_engine (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) engine = vllm.AsyncLLMEngine.from_engine_args(engine_args, stat_loggers=stat_loggers) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/async_llm.py", line 251, in from_engine_args (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) return cls( (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) ^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/async_llm.py", line 148, in __init__ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) self.engine_core = EngineCoreClient.make_async_mp_client( (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 124, in make_async_mp_client (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) return AsyncMPClient(*client_args) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 835, in __init__ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) super().__init__( (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 490, in __init__ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) with launch_core_engines(vllm_config, executor_class, log_stats) as ( (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/contextlib.py", line 144, in __exit__ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) next(self.gen) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/utils.py", line 936, in launch_core_engines (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) wait_for_engine_startup( (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/utils.py", line 995, in wait_for_engine_startup (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) raise RuntimeError( (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) RuntimeError: Engine core initialization failed. See root cause above. Failed core proc(s): {} (AsyncVLLMInferenceEngine pid=2796151, ip=10.128.32.45) (EngineCore_DP0 pid=2796398) Loading safetensors checkpoint shards: 75% Completed | 3/4 [00:03<00:01, 1.26s/it] [repeated 33x across cluster] (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) [pynccl] dumped 0 entries to /e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps/nccl_trace_pynccl_pid2958691 (reason=atexit) (FSDPPolicyWorkerBase pid=294462) `torch_dtype` is deprecated! Use `dtype` instead! [repeated 7x across cluster] (AsyncVLLMInferenceEngine pid=2796151, ip=10.128.32.45) (EngineCore_DP0 pid=2796398) (FSDPPolicyWorkerBase pid=294463) Loading checkpoint shards: 0%| | 0/4 [00:00 [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) 2026-06-07 02:22:13.432 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:133 - setup_envvars_for_vllm: numa_enabled=True [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) 2026-06-07 02:22:13.432 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:setup_envvars_for_vllm:136 - setup_envvars_for_vllm: set VLLM_ENABLE_V1_MULTIPROCESSING=0 for NUMA affinity [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) (EngineCore_DP0 pid=2578420) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=2541854, ip=10.128.32.40) (EngineCore_DP0 pid=2542230) (AsyncVLLMInferenceEngine pid=2796016, ip=10.128.32.45) (EngineCore_DP0 pid=2796354) The tokenizer you are loading from '/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 5x across cluster] (AsyncVLLMInferenceEngine pid=2541994, ip=10.128.32.40) (EngineCore_DP0 pid=2542240) (AsyncVLLMInferenceEngine pid=2541995, ip=10.128.32.40) (EngineCore_DP0 pid=2542222) (AsyncVLLMInferenceEngine pid=2542123, ip=10.128.32.40) (EngineCore_DP0 pid=2542234) (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) 2026-06-07 02:22:14.788 | INFO | skyrl_train.utils.numa:set_numa_affinity_for_gpu:340 - NUMA affinity: bound process to CPUs 216-287 (NUMA node 3) for GPU 3 [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) 2026-06-07 02:22:14.816 | DEBUG | skyrl_train.utils.numa:_set_membind_via_libnuma:375 - NUMA affinity: set memory preferred to NUMA node 3 [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) 2026-06-07 02:22:14.816 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:584 - BaseVLLMInferenceEngine: vllm_v1_disable_multiproc=True, vllm.__version__=dev, VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) 2026-06-07 02:22:14.816 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:__init__:592 - BaseVLLMInferenceEngine: set VLLM_ENABLE_V1_MULTIPROCESSING=0 [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) 2026-06-07 02:22:14.816 | WARNING | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1158 - OpenAI API sampling params overridden: temperature=0.7, top_p=0.95, top_k=20 [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) 2026-06-07 02:22:14.850 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1210 - Engine startup stagger: sleeping 1.60s (attempt 1/5) to avoid port collisions [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2578050, ip=10.128.32.41) (EngineCore_DP0 pid=2578406) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) (EngineCore_DP0 pid=2975804) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 10.128.32.33 (routable head IP) for coordinator litellm base_url connectivity (skyrl_entrypoint pid=294281) 2026-06-07 02:22:27.021 | INFO  | examples.terminal_bench.rollout_coordinator:__init__:405 - [RolloutDispatcher] configured num_coordinators=4, cpus_per_coordinator=8 (skyrl_entrypoint pid=294281) 2026-06-07 02:22:27.059 | INFO  | examples.terminal_bench.rollout_coordinator:startup:434 - [RolloutDispatcher] PlacementGroup ready: 4 bundles x 8 CPU (SPREAD) (raylet, ip=10.128.32.38) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e (FSDPPolicyWorkerBase pid=294462) [rank7]:[W607 02:22:24.789186688 Utils.hpp:137] Warning: Environment variable TORCH_NCCL_TRACE_BUFFER_SIZE is deprecated; use TORCH_FR_BUFFER_SIZE instead (function operator()) [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) (EngineCore_DP0 pid=2626905) Loading safetensors checkpoint shards: 75% Completed | 3/4 [00:11<00:03, 3.91s/it] [repeated 46x across cluster] (AsyncVLLMInferenceEngine pid=2958820, ip=10.128.32.39) (EngineCore_DP0 pid=2959054) (AsyncVLLMInferenceEngine pid=2958818, ip=10.128.32.39) (EngineCore_DP0 pid=2959050) (AsyncVLLMInferenceEngine pid=2958819, ip=10.128.32.39) (EngineCore_DP0 pid=2959046) (AsyncVLLMInferenceEngine pid=2704166, ip=10.128.32.34) (EngineCore_DP0 pid=2704543) (AsyncVLLMInferenceEngine pid=2704295, ip=10.128.32.34) (EngineCore_DP0 pid=2704527) (AsyncVLLMInferenceEngine pid=2704294, ip=10.128.32.34) (EngineCore_DP0 pid=2704539) (AsyncVLLMInferenceEngine pid=2704296, ip=10.128.32.34) (EngineCore_DP0 pid=2704525) (AsyncVLLMInferenceEngine pid=2626529, ip=10.128.32.46) (EngineCore_DP0 pid=2626901) (AsyncVLLMInferenceEngine pid=2669551, ip=10.128.32.38) 2026-06-07 02:22:27.290 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1267 - Initializing OpenAIServingChat with custom_chat_template read from: chat_templates/qwen3_thinking_acc.jinja2 [repeated 15x across cluster] (AsyncVLLMInferenceEngine pid=2626657, ip=10.128.32.46) (EngineCore_DP0 pid=2626889) (AsyncVLLMInferenceEngine pid=2626656, ip=10.128.32.46) (EngineCore_DP0 pid=2626885) (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) (EngineCore_DP0 pid=2626905) (AsyncVLLMInferenceEngine pid=2975429, ip=10.128.32.44) (EngineCore_DP0 pid=2975795) (AsyncVLLMInferenceEngine pid=2669552, ip=10.128.32.38) (EngineCore_DP0 pid=2669784) The tokenizer you are loading from '/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 12x across cluster] (AsyncVLLMInferenceEngine pid=2975564, ip=10.128.32.44) (EngineCore_DP0 pid=2975800) (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) (EngineCore_DP0 pid=2975804) (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) (EngineCore_DP0 pid=2975787) (FSDPPolicyWorkerBase pid=2662807, ip=10.128.32.43) [2026-06-07 02:22:30,830 E 2662807 2662947] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 (RolloutCoordinator pid=2669976, ip=10.128.32.38) 2026-06-07 02:22:32.049 | INFO | examples.terminal_bench.rollout_coordinator:_scale_terminal_bench_cfg:121 - [RolloutCoordinator] scaled n_concurrent_trials 675 -> 168 (// 4) (RolloutCoordinator pid=2669976, ip=10.128.32.38) 2026-06-07 02:22:32.261 | INFO | examples.terminal_bench.terminal_bench_generator:_configure_harbor_logging:236 - Harbor logging level set to INFO (RolloutCoordinator pid=2669976, ip=10.128.32.38) 2026-06-07 02:22:32.261 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:136 - TerminalBenchGenerator initialized with HarborConfigBuilder. Exposed fields: ['name', 'max_episodes', 'enable_summarize', 'store_all_messages', 'trajectory_config', 'enable_episode_logging', 'record_terminal_session', 'enable_pane_logging', 'strict_json_parser', 'interleaved_thinking', 'extra_body', 'override_timeout_sec', 'override_cpus', 'override_memory_mb', 'override_storage_mb', 'auto_snapshot', 'verifier_override_timeout_sec', 'max_retries', 'min_wait_sec', 'max_wait_sec', 'wait_multiplier', 'exclude_exceptions', 'n_concurrent_trials', 'log_level', 'enable_reward_shaping', 'enable_error_classification', 'mask_exceptions', 'default_error_treatment', 'passthrough_exceptions', 'zero_exceptions']. Retry config: max_retries=3, backoff=60.0-600.0s. Concurrent trials: 168. Reward shaping: enabled=False, shaper=pass_ratio. Error classification: enabled=True (RolloutCoordinator pid=2669976, ip=10.128.32.38) 2026-06-07 02:22:32.261 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:152 - TerminalBenchGenerator initialized with custom chat template read from: chat_templates/qwen3_thinking_acc.jinja2 (RolloutCoordinator pid=2669976, ip=10.128.32.38) 2026-06-07 02:22:32.261 | INFO | examples.terminal_bench.rollout_coordinator:__init__:246 - [RolloutCoordinator 0/4] constructed (http=10.128.32.33:8000) (RolloutCoordinator pid=2669976, ip=10.128.32.38) 2026-06-07 02:22:32.265 | INFO | examples.terminal_bench.terminal_bench_generator:_create_orchestrator:292 - QueueOrchestrator created and started with n_concurrent_trials=168, rollback_hook registered for ContextLengthExceededError/AgentTimeoutError (RolloutCoordinator pid=2669976, ip=10.128.32.38) 2026-06-07 02:22:32.265 | INFO | examples.terminal_bench.terminal_bench_generator:startup:249 - TerminalBenchGenerator startup complete. Shared orchestrator ready with n_concurrent_trials=168 (RolloutCoordinator pid=2669976, ip=10.128.32.38) 2026-06-07 02:22:32.265 | INFO | examples.terminal_bench.rollout_coordinator:startup:254 - [RolloutCoordinator 0] startup complete (raylet, ip=10.128.32.38) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 5x across cluster] (skyrl_entrypoint pid=294281) 2026-06-07 02:22:32.266 | INFO  | examples.terminal_bench.rollout_coordinator:startup:469 - [RolloutDispatcher] coordinator 1/4 started (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) (EngineCore_DP0 pid=2975787) Loading safetensors checkpoint shards: 100% Completed | 4/4 [00:13<00:00, 3.28s/it] [repeated 38x across cluster] (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) 2026-06-07 02:22:32.541 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1267 - Initializing OpenAIServingChat with custom_chat_template read from: chat_templates/qwen3_thinking_acc.jinja2 [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) (EngineCore_DP0 pid=864324) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/__init__.py:1617: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.) (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) (EngineCore_DP0 pid=864324) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=864077, ip=10.128.32.35) (EngineCore_DP0 pid=864319) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) (EngineCore_DP0 pid=864313) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=2578050, ip=10.128.32.41) (EngineCore_DP0 pid=2578406) (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) (EngineCore_DP0 pid=2578420) (AsyncVLLMInferenceEngine pid=2578178, ip=10.128.32.41) (EngineCore_DP0 pid=2578410) (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) [W607 02:22:35.858670330 socket.cpp:767] [c10d] The client socket cannot be initialized to connect to [jpbo-041-35.jupiter.internal]:33029 (errno: 97 - Address family not supported by protocol). (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) [W607 02:22:35.862483909 Utils.hpp:166] Warning: Environment variable NCCL_BLOCKING_WAIT is deprecated; use TORCH_NCCL_BLOCKING_WAIT instead (function operator()) (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) [rank0]:[W607 02:22:35.868173189 Utils.hpp:137] Warning: Environment variable TORCH_NCCL_TRACE_BUFFER_SIZE is deprecated; use TORCH_FR_BUFFER_SIZE instead (function operator()) (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) (EngineCore_DP0 pid=864312) _C._set_float32_matmul_precision(precision) (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) (EngineCore_DP0 pid=864312) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 168 (// 4) (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) 2026-06-07 02:22:38.742 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1267 - Initializing OpenAIServingChat with custom_chat_template read from: chat_templates/qwen3_thinking_acc.jinja2 [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) (EngineCore_DP0 pid=864312) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/__init__.py:1617: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.) [repeated 3x across cluster] (skyrl_entrypoint pid=294281) 2026-06-07 02:22:39.941 | INFO  | examples.terminal_bench.rollout_coordinator:startup:469 - [RolloutDispatcher] coordinator 2/4 started (RolloutCoordinator pid=2542476, ip=10.128.32.40) 2026-06-07 02:22:39.937 | INFO | examples.terminal_bench.terminal_bench_generator:_configure_harbor_logging:236 - Harbor logging level set to INFO (RolloutCoordinator pid=2542476, ip=10.128.32.40) 2026-06-07 02:22:39.937 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:136 - TerminalBenchGenerator initialized with HarborConfigBuilder. Exposed fields: ['name', 'max_episodes', 'enable_summarize', 'store_all_messages', 'trajectory_config', 'enable_episode_logging', 'record_terminal_session', 'enable_pane_logging', 'strict_json_parser', 'interleaved_thinking', 'extra_body', 'override_timeout_sec', 'override_cpus', 'override_memory_mb', 'override_storage_mb', 'auto_snapshot', 'verifier_override_timeout_sec', 'max_retries', 'min_wait_sec', 'max_wait_sec', 'wait_multiplier', 'exclude_exceptions', 'n_concurrent_trials', 'log_level', 'enable_reward_shaping', 'enable_error_classification', 'mask_exceptions', 'default_error_treatment', 'passthrough_exceptions', 'zero_exceptions']. Retry config: max_retries=3, backoff=60.0-600.0s. Concurrent trials: 168. Reward shaping: enabled=False, shaper=pass_ratio. Error classification: enabled=True (RolloutCoordinator pid=2542476, ip=10.128.32.40) 2026-06-07 02:22:39.937 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:152 - TerminalBenchGenerator initialized with custom chat template read from: chat_templates/qwen3_thinking_acc.jinja2 (RolloutCoordinator pid=2542476, ip=10.128.32.40) 2026-06-07 02:22:39.937 | INFO | examples.terminal_bench.rollout_coordinator:__init__:246 - [RolloutCoordinator 1/4] constructed (http=10.128.32.33:8000) (RolloutCoordinator pid=2542476, ip=10.128.32.40) 2026-06-07 02:22:39.940 | INFO | examples.terminal_bench.terminal_bench_generator:_create_orchestrator:292 - QueueOrchestrator created and started with n_concurrent_trials=168, rollback_hook registered for ContextLengthExceededError/AgentTimeoutError (RolloutCoordinator pid=2542476, ip=10.128.32.40) 2026-06-07 02:22:39.940 | INFO | examples.terminal_bench.terminal_bench_generator:startup:249 - TerminalBenchGenerator startup complete. Shared orchestrator ready with n_concurrent_trials=168 (RolloutCoordinator pid=2542476, ip=10.128.32.40) 2026-06-07 02:22:39.940 | INFO | examples.terminal_bench.rollout_coordinator:startup:254 - [RolloutCoordinator 1] startup complete (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) [W607 02:22:35.208951015 socket.cpp:767] [c10d] The client socket cannot be initialized to connect to [jpbo-041-35-interconnect-1.jupiter.internal]:40633 (errno: 97 - Address family not supported by protocol). [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) [W607 02:22:35.209434236 Utils.hpp:166] Warning: Environment variable NCCL_BLOCKING_WAIT is deprecated; use TORCH_NCCL_BLOCKING_WAIT instead (function operator()) [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) [rank0]:[W607 02:22:35.211722249 Utils.hpp:137] Warning: Environment variable TORCH_NCCL_TRACE_BUFFER_SIZE is deprecated; use TORCH_FR_BUFFER_SIZE instead (function operator()) [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) (EngineCore_DP0 pid=864313) Loading safetensors checkpoint shards: 0% Completed | 0/4 [00:00 168 (// 4) (RolloutCoordinator pid=2596821, ip=10.128.32.36) The tokenizer you are loading from '/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. (RolloutCoordinator pid=2596821, ip=10.128.32.36) 2026-06-07 02:22:48.257 | INFO | examples.terminal_bench.terminal_bench_generator:_configure_harbor_logging:236 - Harbor logging level set to INFO (RolloutCoordinator pid=2596821, ip=10.128.32.36) 2026-06-07 02:22:48.257 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:136 - TerminalBenchGenerator initialized with HarborConfigBuilder. Exposed fields: ['name', 'max_episodes', 'enable_summarize', 'store_all_messages', 'trajectory_config', 'enable_episode_logging', 'record_terminal_session', 'enable_pane_logging', 'strict_json_parser', 'interleaved_thinking', 'extra_body', 'override_timeout_sec', 'override_cpus', 'override_memory_mb', 'override_storage_mb', 'auto_snapshot', 'verifier_override_timeout_sec', 'max_retries', 'min_wait_sec', 'max_wait_sec', 'wait_multiplier', 'exclude_exceptions', 'n_concurrent_trials', 'log_level', 'enable_reward_shaping', 'enable_error_classification', 'mask_exceptions', 'default_error_treatment', 'passthrough_exceptions', 'zero_exceptions']. Retry config: max_retries=3, backoff=60.0-600.0s. Concurrent trials: 168. Reward shaping: enabled=False, shaper=pass_ratio. Error classification: enabled=True (RolloutCoordinator pid=2596821, ip=10.128.32.36) 2026-06-07 02:22:48.258 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:152 - TerminalBenchGenerator initialized with custom chat template read from: chat_templates/qwen3_thinking_acc.jinja2 (RolloutCoordinator pid=2596821, ip=10.128.32.36) 2026-06-07 02:22:48.258 | INFO | examples.terminal_bench.rollout_coordinator:__init__:246 - [RolloutCoordinator 2/4] constructed (http=10.128.32.33:8000) (RolloutCoordinator pid=2596821, ip=10.128.32.36) 2026-06-07 02:22:48.260 | INFO | examples.terminal_bench.terminal_bench_generator:_create_orchestrator:292 - QueueOrchestrator created and started with n_concurrent_trials=168, rollback_hook registered for ContextLengthExceededError/AgentTimeoutError (RolloutCoordinator pid=2596821, ip=10.128.32.36) 2026-06-07 02:22:48.261 | INFO | examples.terminal_bench.terminal_bench_generator:startup:249 - TerminalBenchGenerator startup complete. Shared orchestrator ready with n_concurrent_trials=168 (RolloutCoordinator pid=2596821, ip=10.128.32.36) 2026-06-07 02:22:48.261 | INFO | examples.terminal_bench.rollout_coordinator:startup:254 - [RolloutCoordinator 2] startup complete (skyrl_entrypoint pid=294281) 2026-06-07 02:22:48.262 | INFO  | examples.terminal_bench.rollout_coordinator:startup:469 - [RolloutDispatcher] coordinator 3/4 started (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) (EngineCore_DP0 pid=864312) (raylet, ip=10.128.32.37) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) (EngineCore_DP0 pid=864312) Loading safetensors checkpoint shards: 100% Completed | 4/4 [00:13<00:00, 3.36s/it] [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) (EngineCore_DP0 pid=864324) (AsyncVLLMInferenceEngine pid=864077, ip=10.128.32.35) (EngineCore_DP0 pid=864319) (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) (EngineCore_DP0 pid=864313) (raylet, ip=10.128.32.37) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) (EngineCore_DP0 pid=864312) The tokenizer you are loading from '/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. (AsyncVLLMInferenceEngine pid=864077, ip=10.128.32.35) (EngineCore_DP0 pid=864319) The tokenizer you are loading from '/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) 2026-06-07 02:22:54.394 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1267 - Initializing OpenAIServingChat with custom_chat_template read from: chat_templates/qwen3_thinking_acc.jinja2 (RolloutCoordinator pid=987693, ip=10.128.32.37) 2026-06-07 02:22:56.126 | INFO | examples.terminal_bench.rollout_coordinator:_scale_terminal_bench_cfg:121 - [RolloutCoordinator] scaled n_concurrent_trials 675 -> 168 (// 4) (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) (EngineCore_DP0 pid=864313) Loading safetensors checkpoint shards: 100% Completed | 4/4 [00:13<00:00, 3.36s/it] [repeated 6x across cluster] (raylet, ip=10.128.32.37) [proxychains] DLL init: proxychains-ng 4.17-git-9-g78ead0e [repeated 4x across cluster] (skyrl_entrypoint pid=294281) 2026-06-07 02:22:56.354 | INFO  | examples.terminal_bench.rollout_coordinator:startup:469 - [RolloutDispatcher] coordinator 4/4 started (skyrl_entrypoint pid=294281) 2026-06-07 02:22:56.354 | INFO  | examples.terminal_bench.rollout_coordinator:startup:477 - [RolloutDispatcher] 4 coordinators started (skyrl_entrypoint pid=294281) 2026-06-07 02:22:56.354 | INFO  | skyrl_train.fully_async_trainer:train:485 - Generator startup complete (skyrl_entrypoint pid=294281) 2026-06-07 02:22:56.354 | INFO  | skyrl_train.fully_async_trainer:_train_loop:510 - Started: 'load_checkpoints' (skyrl_entrypoint pid=294281) 2026-06-07 02:22:56.363 | INFO  | skyrl_train.trainer:load_checkpoints:1664 - Loading checkpoint from: /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/checkpoints/global_step_28 (skyrl_entrypoint pid=294281) 2026-06-07 02:22:56.363 | INFO  | skyrl_train.trainer:load_checkpoints:1670 - Resuming from global_step: 28 (skyrl_entrypoint pid=294281) 2026-06-07 02:22:56.383 | INFO  | skyrl_train.trainer:load_checkpoints:1686 - Successfully loaded trainer state (RolloutCoordinator pid=987693, ip=10.128.32.37) 2026-06-07 02:22:56.349 | INFO | examples.terminal_bench.terminal_bench_generator:_configure_harbor_logging:236 - Harbor logging level set to INFO (RolloutCoordinator pid=987693, ip=10.128.32.37) 2026-06-07 02:22:56.350 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:136 - TerminalBenchGenerator initialized with HarborConfigBuilder. Exposed fields: ['name', 'max_episodes', 'enable_summarize', 'store_all_messages', 'trajectory_config', 'enable_episode_logging', 'record_terminal_session', 'enable_pane_logging', 'strict_json_parser', 'interleaved_thinking', 'extra_body', 'override_timeout_sec', 'override_cpus', 'override_memory_mb', 'override_storage_mb', 'auto_snapshot', 'verifier_override_timeout_sec', 'max_retries', 'min_wait_sec', 'max_wait_sec', 'wait_multiplier', 'exclude_exceptions', 'n_concurrent_trials', 'log_level', 'enable_reward_shaping', 'enable_error_classification', 'mask_exceptions', 'default_error_treatment', 'passthrough_exceptions', 'zero_exceptions']. Retry config: max_retries=3, backoff=60.0-600.0s. Concurrent trials: 168. Reward shaping: enabled=False, shaper=pass_ratio. Error classification: enabled=True (RolloutCoordinator pid=987693, ip=10.128.32.37) 2026-06-07 02:22:56.350 | INFO | examples.terminal_bench.terminal_bench_generator:__init__:152 - TerminalBenchGenerator initialized with custom chat template read from: chat_templates/qwen3_thinking_acc.jinja2 (RolloutCoordinator pid=987693, ip=10.128.32.37) 2026-06-07 02:22:56.350 | INFO | examples.terminal_bench.rollout_coordinator:__init__:246 - [RolloutCoordinator 3/4] constructed (http=10.128.32.33:8000) (RolloutCoordinator pid=987693, ip=10.128.32.37) 2026-06-07 02:22:56.353 | INFO | examples.terminal_bench.terminal_bench_generator:_create_orchestrator:292 - QueueOrchestrator created and started with n_concurrent_trials=168, rollback_hook registered for ContextLengthExceededError/AgentTimeoutError (RolloutCoordinator pid=987693, ip=10.128.32.37) 2026-06-07 02:22:56.353 | INFO | examples.terminal_bench.terminal_bench_generator:startup:249 - TerminalBenchGenerator startup complete. Shared orchestrator ready with n_concurrent_trials=168 (RolloutCoordinator pid=987693, ip=10.128.32.37) 2026-06-07 02:22:56.353 | INFO | examples.terminal_bench.rollout_coordinator:startup:254 - [RolloutCoordinator 3] startup complete (skyrl_entrypoint pid=294281) 2026-06-07 02:22:56.392 | INFO  | skyrl_train.trainer:load_checkpoints:1696 - Successfully loaded dataloader state (skyrl_entrypoint pid=294281) 2026-06-07 02:22:56.392 | INFO  | skyrl_train.trainer:load_checkpoints:1705 - Loading policy checkpoint from /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/checkpoints/global_step_28/policy (RolloutCoordinator pid=2669976, ip=10.128.32.38) [2026-06-07 02:22:57,810 E 2669976 2670068] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 (RolloutCoordinator pid=987693, ip=10.128.32.37) The tokenizer you are loading from '/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6' with an incorrect regex pattern: https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503/discussions/84#69121093e8b480e709447d5e. This will lead to incorrect tokenization. You should set the `fix_mistral_regex=True` flag when loading this tokenizer to fix this issue. [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) 2026-06-07 02:22:54.477 | INFO | skyrl_train.inference_engines.vllm.vllm_engine:_create_engine:1267 - Initializing OpenAIServingChat with custom_chat_template read from: chat_templates/qwen3_thinking_acc.jinja2 [repeated 3x across cluster] (RolloutCoordinator pid=2542476, ip=10.128.32.40) [2026-06-07 02:23:05,084 E 2542476 2542516] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 (RolloutCoordinator pid=2596821, ip=10.128.32.36) [2026-06-07 02:23:12,865 E 2596821 2596861] core_worker_process.cc:842: Failed to establish connection to the metrics exporter agent. Metrics will not be exported. Exporter agent status: RpcError: Running out of retries to initialize the metrics agent. rpc_code: 14 (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4876: UserWarning: barrier(): using the device under current context. You can specify `device_id` in `init_process_group` to mute this warning. (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) warnings.warn( # warn only once (skyrl_entrypoint pid=294281) 2026-06-07 02:23:15.648 | INFO  | skyrl_train.trainer:load_checkpoints:1715 - Successfully loaded policy checkpoint (skyrl_entrypoint pid=294281) 2026-06-07 02:23:15.648 | INFO  | skyrl_train.trainer:load_checkpoints:1731 - Successfully loaded complete checkpoint state from global_step_28 (skyrl_entrypoint pid=294281) 2026-06-07 02:23:15.648 | INFO  | skyrl_train.fully_async_trainer:_train_loop:512 - Resumed training from global_step 28 (skyrl_entrypoint pid=294281) 2026-06-07 02:23:15.663 | INFO  | skyrl_train.utils.data_tracker:load_state:97 - Loaded data tracker state: epoch=0, consumed_in_epoch=1792, total_consumed=1792 (skyrl_entrypoint pid=294281) 2026-06-07 02:23:15.664 | INFO  | skyrl_train.fully_async_trainer:_train_loop:510 - Finished: 'load_checkpoints', time cost: 19.31s (skyrl_entrypoint pid=294281) 2026-06-07 02:23:15.664 | INFO  | skyrl_train.fully_async_trainer:_train_loop:544 - Started: 'init_weight_sync_state' (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) No module named 'vllm._version' (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) from .version import __version__, __version_tuple__ # isort:skip (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) 2026-06-07 02:23:19.911 | INFO  | logging:info:2216 - [weight-sync] Using master_addr=10.128.32.43, master_port=46453 (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) [rank0]:[W607 02:23:19.180220203 socket.cpp:767] [c10d] The client socket cannot be initialized to connect to [jpbo-041-43.jupiter.internal]:46453 (errno: 97 - Address family not supported by protocol). (skyrl_entrypoint pid=294281) 2026-06-07 02:23:20.003 | INFO  | skyrl_train.fully_async_trainer:_train_loop:544 - Finished: 'init_weight_sync_state', time cost: 4.34s (skyrl_entrypoint pid=294281) 2026-06-07 02:23:20.003 | ERROR  | skyrl_train.fully_async_trainer:train:493 - Train loop failed at global_step 28: init_weight_sync_state failed at Ray boundary: RayTaskError(RuntimeError)(RuntimeError('tp_size() failed at Ray boundary: ActorDiedError(RayTaskError(\'__init__\', \'Traceback (most recent call last):\\n File "python/ray/_raylet.pyx", line 1722, in ray._raylet.execute_task\\n File "python/ray/_raylet.pyx", line 1659, in ray._raylet.execute_task.function_executor\\n File "python/ray/_raylet.pyx", line 4342, in ray._raylet.CoreWorker.run_async_func_or_coro_in_event_loop\\n File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/concurrent/futures/_base.py", line 449, in result\\n return self.__get_result()\\n ^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result\\n raise self._exception\\n File "python/ray/_raylet.pyx", line 4329, in async_func\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/async_compat.py", line 52, in wrapper\\n return func(*args, **kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/function_manager.py", line 693, in actor_method_executor\\n return method(__ray_actor, *args, **kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/util/tracing/tracing_helper.py", line 461, in _resume_span\\n return method(self, *_args, **_kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 1139, in __init__\\n super().__init__(*args, **kwargs)\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 603, in __init__\\n self.llm = self._create_engine(*args, **kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/util/tracing/tracing_helper.py", line 461, in _resume_span\\n return method(self, *_args, **_kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 1216, in _create_engine\\n engine = vllm.AsyncLLMEngine.from_engine_args(engine_args, stat_loggers=stat_loggers)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/async_llm.py", line 251, in from_engine_args\\n return cls(\\n ^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/async_llm.py", line 148, in __init__\\n self.engine_core = EngineCoreClient.make_async_mp_client(\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 124, in make_async_mp_client\\n return AsyncMPClient(*client_args)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 835, in __init__\\n super().__init__(\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 490, in __init__\\n with launch_core_engines(vllm_config, executor_class, log_stats) as (\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/contextlib.py", line 144, in __exit__\\n next(self.gen)\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/utils.py", line 936, in launch_core_engines\\n wait_for_engine_startup(\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/utils.py", line 995, in wait_for_engine_startup\\n raise RuntimeError(\\nRuntimeError: Engine core initialization failed. See root cause above. Failed core proc(s): {}\\n\', RuntimeError(\'Engine core initialization failed. See root cause above. Failed core proc(s): {}\'), \'ray::AsyncVLLMInferenceEngine.__init__\', None, None))')) (skyrl_entrypoint pid=294281) Traceback (most recent call last): (skyrl_entrypoint pid=294281) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/fully_async_trainer.py", line 491, in train (skyrl_entrypoint pid=294281) await self._train_loop() (skyrl_entrypoint pid=294281) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/fully_async_trainer.py", line 545, in _train_loop (skyrl_entrypoint pid=294281) self.init_weight_sync_state() (skyrl_entrypoint pid=294281) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/trainer.py", line 851, in init_weight_sync_state (skyrl_entrypoint pid=294281) raise RuntimeError( (skyrl_entrypoint pid=294281) RuntimeError: init_weight_sync_state failed at Ray boundary: RayTaskError(RuntimeError)(RuntimeError('tp_size() failed at Ray boundary: ActorDiedError(RayTaskError(\'__init__\', \'Traceback (most recent call last):\\n File "python/ray/_raylet.pyx", line 1722, in ray._raylet.execute_task\\n File "python/ray/_raylet.pyx", line 1659, in ray._raylet.execute_task.function_executor\\n File "python/ray/_raylet.pyx", line 4342, in ray._raylet.CoreWorker.run_async_func_or_coro_in_event_loop\\n File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/concurrent/futures/_base.py", line 449, in result\\n return self.__get_result()\\n ^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result\\n raise self._exception\\n File "python/ray/_raylet.pyx", line 4329, in async_func\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/async_compat.py", line 52, in wrapper\\n return func(*args, **kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/function_manager.py", line 693, in actor_method_executor\\n return method(__ray_actor, *args, **kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/util/tracing/tracing_helper.py", line 461, in _resume_span\\n return method(self, *_args, **_kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 1139, in __init__\\n super().__init__(*args, **kwargs)\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 603, in __init__\\n self.llm = self._create_engine(*args, **kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/util/tracing/tracing_helper.py", line 461, in _resume_span\\n return method(self, *_args, **_kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 1216, in _create_engine\\n engine = vllm.AsyncLLMEngine.from_engine_args(engine_args, stat_loggers=stat_loggers)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/async_llm.py", line 251, in from_engine_args\\n return cls(\\n ^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/async_llm.py", line 148, in __init__\\n self.engine_core = EngineCoreClient.make_async_mp_client(\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 124, in make_async_mp_client\\n return AsyncMPClient(*client_args)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 835, in __init__\\n super().__init__(\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 490, in __init__\\n with launch_core_engines(vllm_config, executor_class, log_stats) as (\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/contextlib.py", line 144, in __exit__\\n next(self.gen)\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/utils.py", line 936, in launch_core_engines\\n wait_for_engine_startup(\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/utils.py", line 995, in wait_for_engine_startup\\n raise RuntimeError(\\nRuntimeError: Engine core initialization failed. See root cause above. Failed core proc(s): {}\\n\', RuntimeError(\'Engine core initialization failed. See root cause above. Failed core proc(s): {}\'), \'ray::AsyncVLLMInferenceEngine.__init__\', None, None))')) (AsyncVLLMInferenceEngine pid=2541854, ip=10.128.32.40) (EngineCore_DP0 pid=2542230) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py:470: UserWarning: No model update group to destroy (AsyncVLLMInferenceEngine pid=2541854, ip=10.128.32.40) (EngineCore_DP0 pid=2542230) warnings.warn("No model update group to destroy") (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) 2026-06-07 02:23:19.910 | INFO  | logging:info:2216 - [weight-sync] get_node_ip_address()=10.128.32.43 [repeated 3x across cluster] (FSDPPolicyWorkerBase pid=294462) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/__init__.py:7: RuntimeWarning: Failed to read commit hash: [repeated 7x across cluster] (FSDPPolicyWorkerBase pid=294462) No module named 'vllm._version' [repeated 7x across cluster] (FSDPPolicyWorkerBase pid=294462) from .version import __version__, __version_tuple__ # isort:skip [repeated 7x across cluster] (RolloutCoordinator pid=2542476, ip=10.128.32.40) 2026-06-07 02:23:21.030 | INFO | examples.terminal_bench.terminal_bench_generator:shutdown:363 - Shutting down shared QueueOrchestrator... (RolloutCoordinator pid=2542476, ip=10.128.32.40) 2026-06-07 02:23:21.030 | INFO | examples.terminal_bench.terminal_bench_generator:shutdown:365 - QueueOrchestrator shutdown complete (RolloutCoordinator pid=2542476, ip=10.128.32.40) 2026-06-07 02:23:21.030 | INFO | examples.terminal_bench.rollout_coordinator:shutdown:258 - [RolloutCoordinator 1] shutdown complete (skyrl_entrypoint pid=294281) 2026-06-07 02:23:21.029 | INFO  | skyrl_train.inference_engines.inference_engine_client_http_endpoint:shutdown_server:203 - Server shut down after 2 seconds (skyrl_entrypoint pid=294281) 2026-06-07 02:23:21.029 | INFO  | skyrl_train.trainer:_guarded_sync:226 - HTTP endpoint shutdown complete (skyrl_entrypoint pid=294281) 2026-06-07 02:23:21.033 | INFO  | skyrl_train.trainer:_guarded_async:215 - Generator shutdown complete 2026-06-07 02:23:21.090 | ERROR | __main__:main:134 - Training failed: ray::skyrl_entrypoint() (pid=294281, ip=10.128.32.33) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/examples/terminal_bench/entrypoints/main_tbench.py", line 105, in skyrl_entrypoint exp.run() File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/entrypoints/main_base.py", line 483, in run asyncio.run(trainer.train()) File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/asyncio/runners.py", line 195, in run return runner.run(main) ^^^^^^^^^^^^^^^^ File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/asyncio/runners.py", line 118, in run return self._loop.run_until_complete(task) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/asyncio/base_events.py", line 691, in run_until_complete return future.result() ^^^^^^^^^^^^^^^ File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/fully_async_trainer.py", line 491, in train await self._train_loop() File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/fully_async_trainer.py", line 545, in _train_loop self.init_weight_sync_state() File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/trainer.py", line 851, in init_weight_sync_state raise RuntimeError( RuntimeError: init_weight_sync_state failed at Ray boundary: RayTaskError(RuntimeError)(RuntimeError('tp_size() failed at Ray boundary: ActorDiedError(RayTaskError(\'__init__\', \'Traceback (most recent call last):\\n File "python/ray/_raylet.pyx", line 1722, in ray._raylet.execute_task\\n File "python/ray/_raylet.pyx", line 1659, in ray._raylet.execute_task.function_executor\\n File "python/ray/_raylet.pyx", line 4342, in ray._raylet.CoreWorker.run_async_func_or_coro_in_event_loop\\n File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/concurrent/futures/_base.py", line 449, in result\\n return self.__get_result()\\n ^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result\\n raise self._exception\\n File "python/ray/_raylet.pyx", line 4329, in async_func\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/async_compat.py", line 52, in wrapper\\n return func(*args, **kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/function_manager.py", line 693, in actor_method_executor\\n return method(__ray_actor, *args, **kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/util/tracing/tracing_helper.py", line 461, in _resume_span\\n return method(self, *_args, **_kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 1139, in __init__\\n super().__init__(*args, **kwargs)\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 603, in __init__\\n self.llm = self._create_engine(*args, **kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/util/tracing/tracing_helper.py", line 461, in _resume_span\\n return method(self, *_args, **_kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 1216, in _create_engine\\n engine = vllm.AsyncLLMEngine.from_engine_args(engine_args, stat_loggers=stat_loggers)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/async_llm.py", line 251, in from_engine_args\\n return cls(\\n ^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/async_llm.py", line 148, in __init__\\n self.engine_core = EngineCoreClient.make_async_mp_client(\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 124, in make_async_mp_client\\n return AsyncMPClient(*client_args)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 835, in __init__\\n super().__init__(\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 490, in __init__\\n with launch_core_engines(vllm_config, executor_class, log_stats) as (\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/contextlib.py", line 144, in __exit__\\n next(self.gen)\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/utils.py", line 936, in launch_core_engines\\n wait_for_engine_startup(\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/utils.py", line 995, in wait_for_engine_startup\\n raise RuntimeError(\\nRuntimeError: Engine core initialization failed. See root cause above. Failed core proc(s): {}\\n\', RuntimeError(\'Engine core initialization failed. See root cause above. Failed core proc(s): {}\'), \'ray::AsyncVLLMInferenceEngine.__init__\', None, None))')) 2026-06-07 02:23:21.091 | INFO | __main__:main:137 - Shutting down Ray on head node... (AsyncVLLMInferenceEngine pid=2958820, ip=10.128.32.39) (EngineCore_DP0 pid=2959054) /e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py:470: UserWarning: No model update group to destroy [repeated 27x across cluster] (AsyncVLLMInferenceEngine pid=2958820, ip=10.128.32.39) (EngineCore_DP0 pid=2959054) warnings.warn("No model update group to destroy") [repeated 27x across cluster] (RolloutCoordinator pid=987693, ip=10.128.32.37) 2026-06-07 02:23:21.030 | INFO | examples.terminal_bench.terminal_bench_generator:shutdown:363 - Shutting down shared QueueOrchestrator... [repeated 3x across cluster] (RolloutCoordinator pid=987693, ip=10.128.32.37) 2026-06-07 02:23:21.030 | INFO | examples.terminal_bench.terminal_bench_generator:shutdown:365 - QueueOrchestrator shutdown complete [repeated 3x across cluster] (RolloutCoordinator pid=987693, ip=10.128.32.37) 2026-06-07 02:23:21.030 | INFO | examples.terminal_bench.rollout_coordinator:shutdown:258 - [RolloutCoordinator 3] shutdown complete [repeated 3x across cluster] (skyrl_entrypoint pid=294281) [fd-monitor] Started monitoring (every 120s) (skyrl_entrypoint pid=294281) [fd-monitor] [02:21:02] OK: 50 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) (skyrl_entrypoint pid=294281) [fd-monitor] [02:21:02] OK: RSS 1.38 GiB | node mem 129.1/858.0 GiB used (15.0%), avail 728.9 GiB (skyrl_entrypoint pid=294281) ⚙️ Running in WANDB offline mode (skyrl_entrypoint pid=294281) INFO 06-07 02:21:22 [pynccl.py:178] pynccl trace buffer enabled: size=10000 dump_dir=/e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps flush_interval=0 s (pid=987079, ip=10.128.32.37) INFO 06-07 02:21:39 [pynccl.py:178] pynccl trace buffer enabled: size=10000 dump_dir=/e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps flush_interval=0 s (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) WARNING 06-07 02:21:43 [arg_utils.py:1256] The global random seed is set to 42. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) INFO 06-07 02:21:43 [model.py:529] Resolved architecture: Qwen3ForCausalLM (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) INFO 06-07 02:21:43 [model.py:1549] Using max model len 32768 (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) INFO 06-07 02:21:43 [arg_utils.py:1469] Using ray runtime env (env vars redacted): {'env_vars': {'NCCL_CUMEM_ENABLE': '***', 'NCCL_DEBUG': '***', 'NCCL_SOCKET_FAMILY': '***', 'NCCL_SOCKET_IFNAME': '***', 'RAY_ADDRESS': '***', 'VLLM_ALLOW_INSECURE_SERIALIZATION': '***', 'VLLM_ALLOW_RUNTIME_LORA_UPDATING': '***', 'VLLM_DISABLE_COMPILE_CACHE': '***', 'WANDB_API_KEY': '***'}} (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) INFO 06-07 02:21:43 [scheduler.py:224] Chunked prefill is enabled with max_num_batched_tokens=65536. (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) INFO 06-07 02:21:43 [vllm.py:690] Asynchronous scheduling is enabled. (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) WARNING 06-07 02:21:43 [vllm.py:728] Enforce eager set, overriding optimization level to -O0 (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) INFO 06-07 02:21:43 [vllm.py:846] Cudagraph is disabled under eager mode (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) WARNING 06-07 02:21:44 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) WARNING 06-07 02:21:44 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned (pid=987212, ip=10.128.32.37) INFO 06-07 02:21:44 [pynccl.py:178] pynccl trace buffer enabled: size=10000 dump_dir=/e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps flush_interval=0 s (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) WARNING 06-07 02:21:48 [arg_utils.py:1256] The global random seed is set to 56. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) WARNING 06-07 02:21:48 [arg_utils.py:1256] The global random seed is set to 55. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) INFO 06-07 02:21:48 [model.py:529] Resolved architecture: Qwen3ForCausalLM [repeated 2x across cluster] (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) INFO 06-07 02:21:48 [model.py:1549] Using max model len 32768 [repeated 2x across cluster] (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) INFO 06-07 02:21:48 [arg_utils.py:1469] Using ray runtime env (env vars redacted): {'env_vars': {'NCCL_CUMEM_ENABLE': '***', 'NCCL_DEBUG': '***', 'NCCL_SOCKET_FAMILY': '***', 'NCCL_SOCKET_IFNAME': '***', 'RAY_ADDRESS': '***', 'VLLM_ALLOW_INSECURE_SERIALIZATION': '***', 'VLLM_ALLOW_RUNTIME_LORA_UPDATING': '***', 'VLLM_DISABLE_COMPILE_CACHE': '***', 'WANDB_API_KEY': '***'}} [repeated 2x across cluster] (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) INFO 06-07 02:21:48 [scheduler.py:224] Chunked prefill is enabled with max_num_batched_tokens=65536. [repeated 2x across cluster] (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) INFO 06-07 02:21:48 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 2x across cluster] (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) WARNING 06-07 02:21:48 [vllm.py:728] Enforce eager set, overriding optimization level to -O0 [repeated 2x across cluster] (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) INFO 06-07 02:21:48 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 2x across cluster] (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) WARNING 06-07 02:21:48 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) WARNING 06-07 02:21:48 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) WARNING 06-07 02:21:49 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) WARNING 06-07 02:21:49 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned (pid=3079064, ip=10.128.32.42) INFO 06-07 02:21:48 [pynccl.py:178] pynccl trace buffer enabled: size=10000 dump_dir=/e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps flush_interval=0 s [repeated 18x across cluster] (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) INFO 06-07 02:21:51 [core.py:97] Initializing a V1 LLM engine (vdev) with config: model='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', speculative_config=None, tokenizer='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, 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), seed=42, served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [65536], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, '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': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []} (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) WARNING 06-07 02:21:53 [arg_utils.py:1256] The global random seed is set to 61. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. [repeated 16x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) INFO 06-07 02:21:53 [model.py:529] Resolved architecture: Qwen3ForCausalLM [repeated 16x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) INFO 06-07 02:21:53 [model.py:1549] Using max model len 32768 [repeated 16x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) INFO 06-07 02:21:53 [arg_utils.py:1469] Using ray runtime env (env vars redacted): {'env_vars': {'NCCL_CUMEM_ENABLE': '***', 'NCCL_DEBUG': '***', 'NCCL_SOCKET_FAMILY': '***', 'NCCL_SOCKET_IFNAME': '***', 'RAY_ADDRESS': '***', 'VLLM_ALLOW_INSECURE_SERIALIZATION': '***', 'VLLM_ALLOW_RUNTIME_LORA_UPDATING': '***', 'VLLM_DISABLE_COMPILE_CACHE': '***', 'WANDB_API_KEY': '***'}} [repeated 16x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) INFO 06-07 02:21:53 [scheduler.py:224] Chunked prefill is enabled with max_num_batched_tokens=65536. [repeated 16x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) INFO 06-07 02:21:53 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 16x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) WARNING 06-07 02:21:53 [vllm.py:728] Enforce eager set, overriding optimization level to -O0 [repeated 16x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) INFO 06-07 02:21:53 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 16x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) WARNING 06-07 02:21:53 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 16x across cluster] (AsyncVLLMInferenceEngine pid=3079064, ip=10.128.32.42) WARNING 06-07 02:21:53 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned [repeated 16x across cluster] (pid=2626785, ip=10.128.32.46) INFO 06-07 02:21:55 [pynccl.py:178] pynccl trace buffer enabled: size=10000 dump_dir=/e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps flush_interval=0 s [repeated 10x across cluster] (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) INFO 06-07 02:21:56 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) INFO 06-07 02:21:56 [parallel_state.py:1234] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.32.37:41139 backend=nccl (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) INFO 06-07 02:21:56 [parallel_state.py:1445] 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 (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) (EngineCore_DP0 pid=987447) INFO 06-07 02:21:57 [core.py:97] Initializing a V1 LLM engine (vdev) with config: model='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', speculative_config=None, tokenizer='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, 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), seed=56, served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [65536], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, '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': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []} (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) INFO 06-07 02:21:57 [gpu_model_runner.py:4125] Starting to load model /e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6... (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) INFO 06-07 02:21:58 [cuda.py:367] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. (AsyncVLLMInferenceEngine pid=2626657, ip=10.128.32.46) WARNING 06-07 02:21:58 [arg_utils.py:1256] The global random seed is set to 69. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2626657, ip=10.128.32.46) INFO 06-07 02:21:58 [model.py:529] Resolved architecture: Qwen3ForCausalLM [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2626657, ip=10.128.32.46) INFO 06-07 02:21:58 [model.py:1549] Using max model len 32768 [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2626657, ip=10.128.32.46) INFO 06-07 02:21:58 [arg_utils.py:1469] Using ray runtime env (env vars redacted): {'env_vars': {'NCCL_CUMEM_ENABLE': '***', 'NCCL_DEBUG': '***', 'NCCL_SOCKET_FAMILY': '***', 'NCCL_SOCKET_IFNAME': '***', 'RAY_ADDRESS': '***', 'VLLM_ALLOW_INSECURE_SERIALIZATION': '***', 'VLLM_ALLOW_RUNTIME_LORA_UPDATING': '***', 'VLLM_DISABLE_COMPILE_CACHE': '***', 'WANDB_API_KEY': '***'}} [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2626657, ip=10.128.32.46) INFO 06-07 02:21:58 [scheduler.py:224] Chunked prefill is enabled with max_num_batched_tokens=65536. [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2626657, ip=10.128.32.46) INFO 06-07 02:21:58 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2626657, ip=10.128.32.46) WARNING 06-07 02:21:58 [vllm.py:728] Enforce eager set, overriding optimization level to -O0 [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2626657, ip=10.128.32.46) INFO 06-07 02:21:58 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2626529, ip=10.128.32.46) WARNING 06-07 02:21:59 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2626529, ip=10.128.32.46) WARNING 06-07 02:21:59 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned [repeated 9x across cluster] (pid=2662729, ip=10.128.32.43) ⚙️ Running in WANDB offline mode (pid=2578180, ip=10.128.32.41) INFO 06-07 02:22:00 [pynccl.py:178] pynccl trace buffer enabled: size=10000 dump_dir=/e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps flush_interval=0 s [repeated 26x across cluster] (AsyncVLLMInferenceEngine pid=2541854, ip=10.128.32.40) (EngineCore_DP0 pid=2542230) INFO 06-07 02:22:01 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) (EngineCore_DP0 pid=987452) INFO 06-07 02:22:01 [parallel_state.py:1234] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.32.37:50831 backend=nccl [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) (EngineCore_DP0 pid=987452) INFO 06-07 02:22:01 [parallel_state.py:1445] 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 [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2669550, ip=10.128.32.38) (EngineCore_DP0 pid=2669785) INFO 06-07 02:22:01 [core.py:97] Initializing a V1 LLM engine (vdev) with config: model='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', speculative_config=None, tokenizer='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, 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), seed=51, served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [65536], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, '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': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []} [repeated 14x across cluster] (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) (EngineCore_DP0 pid=987452) INFO 06-07 02:22:02 [gpu_model_runner.py:4125] Starting to load model /e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6... [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) (EngineCore_DP0 pid=987452) INFO 06-07 02:22:02 [cuda.py:367] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) WARNING 06-07 02:22:02 [arg_utils.py:1256] The global random seed is set to 84. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. [repeated 13x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) INFO 06-07 02:22:02 [model.py:529] Resolved architecture: Qwen3ForCausalLM [repeated 13x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) INFO 06-07 02:22:02 [model.py:1549] Using max model len 32768 [repeated 13x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) INFO 06-07 02:22:02 [arg_utils.py:1469] Using ray runtime env (env vars redacted): {'env_vars': {'NCCL_CUMEM_ENABLE': '***', 'NCCL_DEBUG': '***', 'NCCL_SOCKET_FAMILY': '***', 'NCCL_SOCKET_IFNAME': '***', 'RAY_ADDRESS': '***', 'VLLM_ALLOW_INSECURE_SERIALIZATION': '***', 'VLLM_ALLOW_RUNTIME_LORA_UPDATING': '***', 'VLLM_DISABLE_COMPILE_CACHE': '***', 'WANDB_API_KEY': '***'}} [repeated 13x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) INFO 06-07 02:22:02 [scheduler.py:224] Chunked prefill is enabled with max_num_batched_tokens=65536. [repeated 13x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) INFO 06-07 02:22:02 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 13x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) WARNING 06-07 02:22:02 [vllm.py:728] Enforce eager set, overriding optimization level to -O0 [repeated 13x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) INFO 06-07 02:22:02 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 13x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) WARNING 06-07 02:22:03 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 12x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) WARNING 06-07 02:22:03 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned [repeated 12x across cluster] (AsyncVLLMInferenceEngine pid=2704294, ip=10.128.32.34) INFO 06-07 02:22:05 [pynccl.py:178] pynccl trace buffer enabled: size=10000 dump_dir=/e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps flush_interval=0 s [repeated 13x across cluster] (AsyncVLLMInferenceEngine pid=3079063, ip=10.128.32.42) (EngineCore_DP0 pid=3079292) INFO 06-07 02:22:06 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2596339, ip=10.128.32.36) (EngineCore_DP0 pid=2596566) INFO 06-07 02:22:06 [parallel_state.py:1234] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.32.36:37763 backend=nccl [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2596339, ip=10.128.32.36) (EngineCore_DP0 pid=2596566) INFO 06-07 02:22:06 [parallel_state.py:1445] 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 [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2704294, ip=10.128.32.34) (EngineCore_DP0 pid=2704539) INFO 06-07 02:22:05 [core.py:97] Initializing a V1 LLM engine (vdev) with config: model='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', speculative_config=None, tokenizer='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, 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), seed=64, served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [65536], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, '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': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []} [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2596340, ip=10.128.32.36) (EngineCore_DP0 pid=2596570) INFO 06-07 02:22:07 [gpu_model_runner.py:4125] Starting to load model /e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6... [repeated 9x across cluster] (pid=2662809, ip=10.128.32.43) ⚙️ Running in WANDB offline mode (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) INFO 06-07 02:22:08 [default_loader.py:293] Loading weights took 9.29 seconds (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) (EngineCore_DP0 pid=987452) INFO 06-07 02:22:08 [gpu_model_runner.py:4222] Model loading took 15.27 GiB memory and 6.143796 seconds (AsyncVLLMInferenceEngine pid=2596340, ip=10.128.32.36) (EngineCore_DP0 pid=2596570) INFO 06-07 02:22:08 [cuda.py:367] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) WARNING 06-07 02:22:05 [arg_utils.py:1256] The global random seed is set to 89. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) INFO 06-07 02:22:06 [model.py:529] Resolved architecture: Qwen3ForCausalLM [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) INFO 06-07 02:22:06 [model.py:1549] Using max model len 32768 [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) INFO 06-07 02:22:06 [arg_utils.py:1469] Using ray runtime env (env vars redacted): {'env_vars': {'NCCL_CUMEM_ENABLE': '***', 'NCCL_DEBUG': '***', 'NCCL_SOCKET_FAMILY': '***', 'NCCL_SOCKET_IFNAME': '***', 'RAY_ADDRESS': '***', 'VLLM_ALLOW_INSECURE_SERIALIZATION': '***', 'VLLM_ALLOW_RUNTIME_LORA_UPDATING': '***', 'VLLM_DISABLE_COMPILE_CACHE': '***', 'WANDB_API_KEY': '***'}} [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) INFO 06-07 02:22:06 [scheduler.py:224] Chunked prefill is enabled with max_num_batched_tokens=65536. [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) INFO 06-07 02:22:06 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) WARNING 06-07 02:22:06 [vllm.py:728] Enforce eager set, overriding optimization level to -O0 [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) INFO 06-07 02:22:06 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) WARNING 06-07 02:22:06 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) WARNING 06-07 02:22:06 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2975429, ip=10.128.32.44) INFO 06-07 02:22:10 [pynccl.py:178] pynccl trace buffer enabled: size=10000 dump_dir=/e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps flush_interval=0 s [repeated 13x across cluster] (AsyncVLLMInferenceEngine pid=2796150, ip=10.128.32.45) (EngineCore_DP0 pid=2796384) INFO 06-07 02:22:10 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) INFO 06-07 02:22:11 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) INFO 06-07 02:22:11 [kv_cache_utils.py:1307] GPU KV cache size: 359,104 tokens (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) INFO 06-07 02:22:11 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x (AsyncVLLMInferenceEngine pid=2796150, ip=10.128.32.45) (EngineCore_DP0 pid=2796384) INFO 06-07 02:22:10 [parallel_state.py:1234] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.32.45:48431 backend=nccl [repeated 10x across cluster] (AsyncVLLMInferenceEngine pid=2796150, ip=10.128.32.45) (EngineCore_DP0 pid=2796384) INFO 06-07 02:22:10 [parallel_state.py:1445] 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 [repeated 10x across cluster] (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) INFO 06-07 02:22:12 [kernel_warmup.py:44] Skipping FlashInfer autotune because it is disabled. (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) INFO 06-07 02:22:12 [core.py:278] init engine (profile, create kv cache, warmup model) took 3.50 seconds (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) (EngineCore_DP0 pid=2975804) INFO 06-07 02:22:12 [core.py:97] Initializing a V1 LLM engine (vdev) with config: model='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', speculative_config=None, tokenizer='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, 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), seed=84, served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [65536], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, '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': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []} [repeated 15x across cluster] (AsyncVLLMInferenceEngine pid=2796150, ip=10.128.32.45) (EngineCore_DP0 pid=2796384) INFO 06-07 02:22:11 [gpu_model_runner.py:4125] Starting to load model /e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6... [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=987079, ip=10.128.32.37) (EngineCore_DP0 pid=987418) WARNING 06-07 02:22:12 [vllm.py:735] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. (AsyncVLLMInferenceEngine pid=987212, ip=10.128.32.37) WARNING 06-07 02:22:12 [model.py:1350] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`. (pid=294462) ⚙️ Running in WANDB offline mode [repeated 6x across cluster] (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) (EngineCore_DP0 pid=987447) INFO 06-07 02:22:08 [default_loader.py:293] Loading weights took 6.05 seconds [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) (EngineCore_DP0 pid=987447) INFO 06-07 02:22:08 [gpu_model_runner.py:4222] Model loading took 15.27 GiB memory and 6.835432 seconds [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2796149, ip=10.128.32.45) (EngineCore_DP0 pid=2796391) INFO 06-07 02:22:13 [cuda.py:367] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) (EngineCore_DP0 pid=987447) INFO 06-07 02:22:12 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) (EngineCore_DP0 pid=987447) INFO 06-07 02:22:12 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) (EngineCore_DP0 pid=987447) WARNING 06-07 02:22:12 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] EngineCore failed to start. (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] Traceback (most recent call last): (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core.py", line 996, in run_engine_core (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] engine_core = EngineCoreProc(*args, engine_index=dp_rank, **kwargs) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core.py", line 740, in __init__ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] super().__init__( (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core.py", line 106, in __init__ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] self.model_executor = executor_class(vllm_config) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] ^^^^^^^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/executor/abstract.py", line 103, in __init__ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] self._init_executor() (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/executor/uniproc_executor.py", line 47, in _init_executor (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] self.driver_worker.init_device() (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/worker/worker_base.py", line 332, in init_device (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] self.worker.init_device() # type: ignore (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] ^^^^^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/worker/gpu_worker.py", line 232, in init_device (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] init_worker_distributed_environment( (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/worker/gpu_worker.py", line 1040, in init_worker_distributed_environment (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] init_distributed_environment( (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/distributed/parallel_state.py", line 1256, in init_distributed_environment (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] torch.distributed.init_process_group( (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/distributed/c10d_logger.py", line 81, in wrapper (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] return func(*args, **kwargs) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] ^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/distributed/c10d_logger.py", line 95, in wrapper (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] func_return = func(*args, **kwargs) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] ^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py", line 1762, in init_process_group (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] store, rank, world_size = next(rendezvous_iterator) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] ^^^^^^^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/distributed/rendezvous.py", line 230, in _tcp_rendezvous_handler (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] store = _create_c10d_store( (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] ^^^^^^^^^^^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/distributed/rendezvous.py", line 198, in _create_c10d_store (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] return TCPStore( (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] ^^^^^^^^^ (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] torch.distributed.DistNetworkError: The server socket has failed to listen on any local network address. port: 44571, useIpv6: false, code: -98, name: EADDRINUSE, message: address already in use (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] Exception raised from makeWithPort at /pytorch/torch/csrc/distributed/c10d/TCPStoreLibUvBackend.cpp:307 (most recent call first): (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #0: c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string, std::allocator >) + 0xb0 (0x40006f4ac700 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libc10.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #1: + 0x5f29220 (0x40004f649220 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #2: + 0x5f4326c (0x40004f66326c in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #3: + 0x5f49074 (0x40004f669074 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #4: + 0x5f49138 (0x40004f669138 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #5: + 0x5f2ccc4 (0x40004f64ccc4 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #6: c10d::TCPStore::TCPStore(std::__cxx11::basic_string, std::allocator >, c10d::TCPStoreOptions const&) + 0x104 (0x40004f651564 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #7: + 0x109a094 (0x4000493fa094 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_python.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #8: + 0x113236c (0x40004949236c in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_python.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #9: + 0x5d6d60 (0x400048936d60 in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_python.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #10: + 0x1b7a38 (0xaaaab8697a38 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #11: _PyObject_MakeTpCall + 0x98 (0xaaaab8645db8 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #12: + 0x169f50 (0xaaaab8649f50 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #13: + 0x1682e4 (0xaaaab86482e4 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #14: + 0x1e0ce8 (0xaaaab86c0ce8 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #15: + 0x1d7ddc (0xaaaab86b7ddc in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #16: + 0x646b0c (0x4000489a6b0c in /e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/torch/lib/libtorch_python.so) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #17: _PyObject_MakeTpCall + 0x98 (0xaaaab8645db8 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #18: _PyEval_EvalFrameDefault + 0x280c (0xaaaab874ae54 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #19: + 0x1808c0 (0xaaaab86608c0 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #20: + 0x182bf8 (0xaaaab8662bf8 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #21: + 0x25fd30 (0xaaaab873fd30 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #22: + 0x1b7d20 (0xaaaab8697d20 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #23: PyObject_Vectorcall + 0x54 (0xaaaab86460e4 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #24: _PyEval_EvalFrameDefault + 0x280c (0xaaaab874ae54 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #25: _PyObject_FastCallDictTstate + 0x80 (0xaaaab8647f20 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #26: _PyObject_Call_Prepend + 0x140 (0xaaaab86481ec in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #27: + 0x1e0d80 (0xaaaab86c0d80 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #28: + 0x1d7ddc (0xaaaab86b7ddc in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #29: _PyObject_MakeTpCall + 0x98 (0xaaaab8645db8 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #30: _PyEval_EvalFrameDefault + 0x280c (0xaaaab874ae54 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #31: _PyObject_FastCallDictTstate + 0x10c (0xaaaab8647fac in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #32: _PyObject_Call_Prepend + 0x140 (0xaaaab86481ec in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #33: + 0x1e0d80 (0xaaaab86c0d80 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #34: + 0x1d7ddc (0xaaaab86b7ddc in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #35: _PyObject_Call + 0x68 (0xaaaab8648488 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #36: _PyEval_EvalFrameDefault + 0x52ac (0xaaaab874d8f4 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #37: PyEval_EvalCode + 0xb4 (0xaaaab8752eb4 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #38: + 0x2ccdcc (0xaaaab87acdcc in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #39: + 0x2ccef4 (0xaaaab87acef4 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #40: PyRun_StringFlags + 0x90 (0xaaaab87b1050 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #41: PyRun_SimpleStringFlags + 0x58 (0xaaaab87b10f8 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #42: Py_RunMain + 0x2c8 (0xaaaab87d9190 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #43: Py_BytesMain + 0x64 (0xaaaab87d9fb4 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #44: + 0x27540 (0x4000379a7540 in /lib64/libc.so.6) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #45: __libc_start_main + 0x98 (0x4000379a7618 in /lib64/libc.so.6) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] frame #46: + 0x10e0c0 (0xaaaab85ee0c0 in VLLM::EngineCore) (AsyncVLLMInferenceEngine pid=2958691, ip=10.128.32.39) (EngineCore_DP0 pid=2959070) ERROR 06-07 02:22:15 [core.py:1006] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) INFO 06-07 02:22:15 [pynccl.py:178] pynccl trace buffer enabled: size=10000 dump_dir=/e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps flush_interval=0 s [repeated 9x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) WARNING 06-07 02:22:16 [arg_utils.py:1256] The global random seed is set to 77. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) INFO 06-07 02:22:16 [model.py:529] Resolved architecture: Qwen3ForCausalLM (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) INFO 06-07 02:22:16 [model.py:1549] Using max model len 32768 (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) INFO 06-07 02:22:16 [arg_utils.py:1469] Using ray runtime env (env vars redacted): {'env_vars': {'NCCL_CUMEM_ENABLE': '***', 'NCCL_DEBUG': '***', 'NCCL_SOCKET_FAMILY': '***', 'NCCL_SOCKET_IFNAME': '***', 'RAY_ADDRESS': '***', 'VLLM_ALLOW_INSECURE_SERIALIZATION': '***', 'VLLM_ALLOW_RUNTIME_LORA_UPDATING': '***', 'VLLM_DISABLE_COMPILE_CACHE': '***', 'WANDB_API_KEY': '***'}} (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) INFO 06-07 02:22:16 [scheduler.py:224] Chunked prefill is enabled with max_num_batched_tokens=65536. (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) WARNING 06-07 02:22:16 [vllm.py:728] Enforce eager set, overriding optimization level to -O0 (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) (EngineCore_DP0 pid=2975804) INFO 06-07 02:22:16 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] [repeated 18x across cluster] (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) (EngineCore_DP0 pid=987447) INFO 06-07 02:22:11 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) (EngineCore_DP0 pid=987447) INFO 06-07 02:22:11 [kv_cache_utils.py:1307] GPU KV cache size: 359,104 tokens [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) (EngineCore_DP0 pid=987447) INFO 06-07 02:22:11 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) (EngineCore_DP0 pid=2975804) INFO 06-07 02:22:16 [parallel_state.py:1234] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.32.44:41207 backend=nccl [repeated 18x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) (EngineCore_DP0 pid=2975804) INFO 06-07 02:22:16 [parallel_state.py:1445] 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 [repeated 17x across cluster] (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) WARNING 06-07 02:22:16 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) (EngineCore_DP0 pid=987447) INFO 06-07 02:22:12 [kernel_warmup.py:44] Skipping FlashInfer autotune because it is disabled. [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) (EngineCore_DP0 pid=987447) INFO 06-07 02:22:12 [core.py:278] init engine (profile, create kv cache, warmup model) took 3.49 seconds [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2578050, ip=10.128.32.41) (EngineCore_DP0 pid=2578406) INFO 06-07 02:22:16 [core.py:97] Initializing a V1 LLM engine (vdev) with config: model='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', speculative_config=None, tokenizer='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, 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), seed=86, served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [65536], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, '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': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []} [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) (EngineCore_DP0 pid=2975804) INFO 06-07 02:22:16 [gpu_model_runner.py:4125] Starting to load model /e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6... [repeated 17x across cluster] (AsyncVLLMInferenceEngine pid=987213, ip=10.128.32.37) (EngineCore_DP0 pid=987447) WARNING 06-07 02:22:12 [vllm.py:735] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=987214, ip=10.128.32.37) WARNING 06-07 02:22:12 [model.py:1350] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`. [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2796149, ip=10.128.32.45) (EngineCore_DP0 pid=2796391) INFO 06-07 02:22:18 [default_loader.py:293] Loading weights took 4.18 seconds [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2796149, ip=10.128.32.45) (EngineCore_DP0 pid=2796391) INFO 06-07 02:22:18 [gpu_model_runner.py:4222] Model loading took 15.27 GiB memory and 4.518817 seconds [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2975565, ip=10.128.32.44) (EngineCore_DP0 pid=2975804) INFO 06-07 02:22:17 [cuda.py:367] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. [repeated 15x across cluster] (AsyncVLLMInferenceEngine pid=2796150, ip=10.128.32.45) (EngineCore_DP0 pid=2796384) INFO 06-07 02:22:19 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 6x across cluster] (AsyncVLLMInferenceEngine pid=2796150, ip=10.128.32.45) (EngineCore_DP0 pid=2796384) INFO 06-07 02:22:19 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 6x across cluster] (AsyncVLLMInferenceEngine pid=2796150, ip=10.128.32.45) (EngineCore_DP0 pid=2796384) WARNING 06-07 02:22:19 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 6x across cluster] (AsyncVLLMInferenceEngine pid=2578050, ip=10.128.32.41) INFO 06-07 02:22:15 [pynccl.py:178] pynccl trace buffer enabled: size=10000 dump_dir=/e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps flush_interval=0 s (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) WARNING 06-07 02:22:17 [arg_utils.py:1256] The global random seed is set to 76. Since VLLM_ENABLE_V1_MULTIPROCESSING is set to False, this may affect the random state of the Python process that launched vLLM. [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) INFO 06-07 02:22:17 [model.py:529] Resolved architecture: Qwen3ForCausalLM [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) INFO 06-07 02:22:17 [model.py:1549] Using max model len 32768 [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) INFO 06-07 02:22:17 [arg_utils.py:1469] Using ray runtime env (env vars redacted): {'env_vars': {'NCCL_CUMEM_ENABLE': '***', 'NCCL_DEBUG': '***', 'NCCL_SOCKET_FAMILY': '***', 'NCCL_SOCKET_IFNAME': '***', 'RAY_ADDRESS': '***', 'VLLM_ALLOW_INSECURE_SERIALIZATION': '***', 'VLLM_ALLOW_RUNTIME_LORA_UPDATING': '***', 'VLLM_DISABLE_COMPILE_CACHE': '***', 'WANDB_API_KEY': '***'}} [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) INFO 06-07 02:22:17 [scheduler.py:224] Chunked prefill is enabled with max_num_batched_tokens=65536. [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) WARNING 06-07 02:22:17 [vllm.py:728] Enforce eager set, overriding optimization level to -O0 [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) INFO 06-07 02:22:20 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2796149, ip=10.128.32.45) (EngineCore_DP0 pid=2796391) INFO 06-07 02:22:20 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2796149, ip=10.128.32.45) (EngineCore_DP0 pid=2796391) INFO 06-07 02:22:20 [kv_cache_utils.py:1307] GPU KV cache size: 359,104 tokens [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2796149, ip=10.128.32.45) (EngineCore_DP0 pid=2796391) INFO 06-07 02:22:20 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) INFO 06-07 02:22:20 [parallel_state.py:1234] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.32.41:43419 backend=nccl [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) INFO 06-07 02:22:20 [parallel_state.py:1445] 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 [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) WARNING 06-07 02:22:17 [system_utils.py:140] We must use the `spawn` multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'. See https://docs.vllm.ai/en/latest/usage/troubleshooting.html#python-multiprocessing for more information. Reasons: In a Ray actor and can only be spawned [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2541854, ip=10.128.32.40) (EngineCore_DP0 pid=2542230) INFO 06-07 02:22:22 [kernel_warmup.py:44] Skipping FlashInfer autotune because it is disabled. [repeated 5x across cluster] (AsyncVLLMInferenceEngine pid=2541854, ip=10.128.32.40) (EngineCore_DP0 pid=2542230) INFO 06-07 02:22:22 [core.py:278] init engine (profile, create kv cache, warmup model) took 2.82 seconds [repeated 5x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) INFO 06-07 02:22:21 [gpu_model_runner.py:4125] Starting to load model /e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6... [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2542123, ip=10.128.32.40) (EngineCore_DP0 pid=2542234) WARNING 06-07 02:22:22 [vllm.py:735] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=2541854, ip=10.128.32.40) WARNING 06-07 02:22:23 [model.py:1350] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`. [repeated 5x across cluster] (AsyncVLLMInferenceEngine pid=2669552, ip=10.128.32.38) (EngineCore_DP0 pid=2669784) INFO 06-07 02:22:23 [default_loader.py:293] Loading weights took 13.40 seconds [repeated 16x across cluster] (AsyncVLLMInferenceEngine pid=2669422, ip=10.128.32.38) (EngineCore_DP0 pid=2669802) INFO 06-07 02:22:23 [gpu_model_runner.py:4222] Model loading took 15.27 GiB memory and 14.574883 seconds [repeated 13x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) INFO 06-07 02:22:21 [cuda.py:367] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. [repeated 4x across cluster] (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) NCCL version 2.27.7+cuda13.0 (AsyncVLLMInferenceEngine pid=2596338, ip=10.128.32.36) (EngineCore_DP0 pid=2596579) INFO 06-07 02:22:25 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 7x across cluster] (AsyncVLLMInferenceEngine pid=2596338, ip=10.128.32.36) (EngineCore_DP0 pid=2596579) INFO 06-07 02:22:25 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 7x across cluster] (AsyncVLLMInferenceEngine pid=2596338, ip=10.128.32.36) (EngineCore_DP0 pid=2596579) WARNING 06-07 02:22:25 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 7x across cluster] (AsyncVLLMInferenceEngine pid=2669551, ip=10.128.32.38) (EngineCore_DP0 pid=2669786) INFO 06-07 02:22:26 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB [repeated 16x across cluster] (AsyncVLLMInferenceEngine pid=2669551, ip=10.128.32.38) (EngineCore_DP0 pid=2669786) INFO 06-07 02:22:26 [kv_cache_utils.py:1307] GPU KV cache size: 359,104 tokens [repeated 16x across cluster] (AsyncVLLMInferenceEngine pid=2669551, ip=10.128.32.38) (EngineCore_DP0 pid=2669786) INFO 06-07 02:22:26 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x [repeated 16x across cluster] (AsyncVLLMInferenceEngine pid=2669551, ip=10.128.32.38) (EngineCore_DP0 pid=2669786) INFO 06-07 02:22:26 [kernel_warmup.py:44] Skipping FlashInfer autotune because it is disabled. [repeated 15x across cluster] (AsyncVLLMInferenceEngine pid=2669552, ip=10.128.32.38) (EngineCore_DP0 pid=2669784) INFO 06-07 02:22:26 [core.py:278] init engine (profile, create kv cache, warmup model) took 2.80 seconds [repeated 15x across cluster] (AsyncVLLMInferenceEngine pid=2669552, ip=10.128.32.38) (EngineCore_DP0 pid=2669784) WARNING 06-07 02:22:27 [vllm.py:735] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. [repeated 12x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) INFO 06-07 02:22:28 [pynccl.py:178] pynccl trace buffer enabled: size=10000 dump_dir=/e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps flush_interval=0 s (AsyncVLLMInferenceEngine pid=2669551, ip=10.128.32.38) WARNING 06-07 02:22:27 [model.py:1350] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`. [repeated 15x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) (EngineCore_DP0 pid=864324) INFO 06-07 02:22:28 [core.py:97] Initializing a V1 LLM engine (vdev) with config: model='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', speculative_config=None, tokenizer='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, 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), seed=76, served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [65536], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, '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': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []} (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) (EngineCore_DP0 pid=2626905) INFO 06-07 02:22:28 [default_loader.py:293] Loading weights took 13.02 seconds [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=2704294, ip=10.128.32.34) (EngineCore_DP0 pid=2704539) INFO 06-07 02:22:28 [gpu_model_runner.py:4222] Model loading took 15.27 GiB memory and 14.076531 seconds [repeated 10x across cluster] (AsyncVLLMInferenceEngine pid=2669552, ip=10.128.32.38) (EngineCore_DP0 pid=2669784) INFO 06-07 02:22:27 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=2669552, ip=10.128.32.38) (EngineCore_DP0 pid=2669784) INFO 06-07 02:22:27 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=2669552, ip=10.128.32.38) (EngineCore_DP0 pid=2669784) WARNING 06-07 02:22:27 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 11x across cluster] (RolloutCoordinator pid=2669976, ip=10.128.32.38) [fd-monitor] Started monitoring (every 120s) (RolloutCoordinator pid=2669976, ip=10.128.32.38) [fd-monitor] [02:22:32] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) (RolloutCoordinator pid=2669976, ip=10.128.32.38) [fd-monitor] [02:22:32] OK: RSS 0.78 GiB | node mem 385.3/858.0 GiB used (44.9%), avail 472.7 GiB (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) (EngineCore_DP0 pid=2626905) INFO 06-07 02:22:31 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) (EngineCore_DP0 pid=2626905) INFO 06-07 02:22:31 [kv_cache_utils.py:1307] GPU KV cache size: 359,104 tokens [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) (EngineCore_DP0 pid=2626905) INFO 06-07 02:22:31 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) (EngineCore_DP0 pid=2626905) INFO 06-07 02:22:31 [kernel_warmup.py:44] Skipping FlashInfer autotune because it is disabled. [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) (EngineCore_DP0 pid=2626905) INFO 06-07 02:22:31 [core.py:278] init engine (profile, create kv cache, warmup model) took 2.82 seconds [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) (EngineCore_DP0 pid=2626905) WARNING 06-07 02:22:32 [vllm.py:735] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) INFO 06-07 02:22:28 [pynccl.py:178] pynccl trace buffer enabled: size=10000 dump_dir=/e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps flush_interval=0 s [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2626785, ip=10.128.32.46) WARNING 06-07 02:22:32 [model.py:1350] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`. [repeated 11x across cluster] (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) (EngineCore_DP0 pid=864312) INFO 06-07 02:22:28 [core.py:97] Initializing a V1 LLM engine (vdev) with config: model='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', speculative_config=None, tokenizer='/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_fallback=False, 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), seed=74, served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'level': None, 'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'splitting_ops': [], 'compile_mm_encoder': False, 'compile_sizes': [], 'compile_ranges_split_points': [65536], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, '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': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, 'eliminate_noops': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []} [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) (EngineCore_DP0 pid=2975787) INFO 06-07 02:22:30 [default_loader.py:293] Loading weights took 13.13 seconds [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) (EngineCore_DP0 pid=2975787) INFO 06-07 02:22:30 [gpu_model_runner.py:4222] Model loading took 15.27 GiB memory and 14.203295 seconds [repeated 8x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) (EngineCore_DP0 pid=864324) INFO 06-07 02:22:34 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) (EngineCore_DP0 pid=864324) INFO 06-07 02:22:35 [parallel_state.py:1234] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.32.35:33029 backend=nccl (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) (EngineCore_DP0 pid=864324) INFO 06-07 02:22:35 [parallel_state.py:1445] 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 (AsyncVLLMInferenceEngine pid=2975564, ip=10.128.32.44) (EngineCore_DP0 pid=2975800) INFO 06-07 02:22:34 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 15x across cluster] (AsyncVLLMInferenceEngine pid=2975564, ip=10.128.32.44) (EngineCore_DP0 pid=2975800) INFO 06-07 02:22:34 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 15x across cluster] (AsyncVLLMInferenceEngine pid=2975564, ip=10.128.32.44) (EngineCore_DP0 pid=2975800) WARNING 06-07 02:22:34 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 15x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) (EngineCore_DP0 pid=864324) INFO 06-07 02:22:35 [gpu_model_runner.py:4125] Starting to load model /e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6... (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) (EngineCore_DP0 pid=864312) INFO 06-07 02:22:36 [cuda.py:367] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) (EngineCore_DP0 pid=2578420) INFO 06-07 02:22:37 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB [repeated 5x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) (EngineCore_DP0 pid=2578420) INFO 06-07 02:22:37 [kv_cache_utils.py:1307] GPU KV cache size: 359,104 tokens [repeated 5x across cluster] (AsyncVLLMInferenceEngine pid=2578179, ip=10.128.32.41) (EngineCore_DP0 pid=2578420) INFO 06-07 02:22:37 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x [repeated 5x across cluster] (AsyncVLLMInferenceEngine pid=2975564, ip=10.128.32.44) (EngineCore_DP0 pid=2975800) INFO 06-07 02:22:33 [kernel_warmup.py:44] Skipping FlashInfer autotune because it is disabled. [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) (EngineCore_DP0 pid=2975787) INFO 06-07 02:22:33 [core.py:278] init engine (profile, create kv cache, warmup model) took 2.80 seconds [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578050, ip=10.128.32.41) (EngineCore_DP0 pid=2578406) WARNING 06-07 02:22:38 [vllm.py:735] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. [repeated 5x across cluster] (AsyncVLLMInferenceEngine pid=2975563, ip=10.128.32.44) WARNING 06-07 02:22:34 [model.py:1350] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`. [repeated 4x across cluster] (RolloutCoordinator pid=2542476, ip=10.128.32.40) [fd-monitor] Started monitoring (every 120s) (RolloutCoordinator pid=2542476, ip=10.128.32.40) [fd-monitor] [02:22:39] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) (RolloutCoordinator pid=2542476, ip=10.128.32.40) [fd-monitor] [02:22:39] OK: RSS 0.78 GiB | node mem 406.2/858.0 GiB used (47.3%), avail 451.7 GiB (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) INFO 06-07 02:22:34 [default_loader.py:293] Loading weights took 12.85 seconds [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) INFO 06-07 02:22:35 [gpu_model_runner.py:4222] Model loading took 15.27 GiB memory and 13.617507 seconds [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) (EngineCore_DP0 pid=864312) INFO 06-07 02:22:35 [worker_base.py:289] Injected into for extended collective_rpc calls ['_apply_fp8_weight_loader_patches', '_is_fp8_model', '_quantize_weights_for_fp8', '_restore_param_subclasses', '_undo_param_subclasses', 'begin_weight_update', 'destroy_weights_update_group', 'end_weight_update', 'init_weight_update_communicator', 'load_weights', 'read_named_weights', 'set_numa_affinity', 'test_rpc'] [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) (EngineCore_DP0 pid=864312) INFO 06-07 02:22:35 [parallel_state.py:1234] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.128.32.35:40633 backend=nccl [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) (EngineCore_DP0 pid=864312) INFO 06-07 02:22:35 [parallel_state.py:1445] 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 [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) INFO 06-07 02:22:38 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) INFO 06-07 02:22:38 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) WARNING 06-07 02:22:38 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) (EngineCore_DP0 pid=864312) INFO 06-07 02:22:35 [gpu_model_runner.py:4125] Starting to load model /e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6... [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) (EngineCore_DP0 pid=864313) INFO 06-07 02:22:36 [cuda.py:367] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) INFO 06-07 02:22:37 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) INFO 06-07 02:22:37 [kv_cache_utils.py:1307] GPU KV cache size: 359,104 tokens [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) INFO 06-07 02:22:37 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) INFO 06-07 02:22:38 [kernel_warmup.py:44] Skipping FlashInfer autotune because it is disabled. [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) INFO 06-07 02:22:38 [core.py:278] init engine (profile, create kv cache, warmup model) took 2.83 seconds [repeated 4x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) (EngineCore_DP0 pid=2578416) WARNING 06-07 02:22:38 [vllm.py:735] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=2578180, ip=10.128.32.41) WARNING 06-07 02:22:38 [model.py:1350] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`. [repeated 4x across cluster] (RolloutCoordinator pid=2596821, ip=10.128.32.36) [fd-monitor] Started monitoring (every 120s) (RolloutCoordinator pid=2596821, ip=10.128.32.36) [fd-monitor] [02:22:48] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) (RolloutCoordinator pid=2596821, ip=10.128.32.36) [fd-monitor] [02:22:48] OK: RSS 0.78 GiB | node mem 394.8/858.0 GiB used (46.0%), avail 463.2 GiB (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) (EngineCore_DP0 pid=864312) INFO 06-07 02:22:50 [default_loader.py:293] Loading weights took 13.45 seconds (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) (EngineCore_DP0 pid=864312) INFO 06-07 02:22:50 [gpu_model_runner.py:4222] Model loading took 15.27 GiB memory and 14.577902 seconds (AsyncVLLMInferenceEngine pid=864077, ip=10.128.32.35) (EngineCore_DP0 pid=864319) INFO 06-07 02:22:53 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB (AsyncVLLMInferenceEngine pid=864077, ip=10.128.32.35) (EngineCore_DP0 pid=864319) INFO 06-07 02:22:53 [kv_cache_utils.py:1307] GPU KV cache size: 359,104 tokens (AsyncVLLMInferenceEngine pid=864077, ip=10.128.32.35) (EngineCore_DP0 pid=864319) INFO 06-07 02:22:53 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) (EngineCore_DP0 pid=864313) INFO 06-07 02:22:53 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) (EngineCore_DP0 pid=864313) INFO 06-07 02:22:53 [kv_cache_utils.py:1307] GPU KV cache size: 359,104 tokens (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) (EngineCore_DP0 pid=864313) INFO 06-07 02:22:53 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x (AsyncVLLMInferenceEngine pid=864077, ip=10.128.32.35) (EngineCore_DP0 pid=864319) INFO 06-07 02:22:53 [kernel_warmup.py:44] Skipping FlashInfer autotune because it is disabled. (AsyncVLLMInferenceEngine pid=864077, ip=10.128.32.35) (EngineCore_DP0 pid=864319) INFO 06-07 02:22:53 [core.py:278] init engine (profile, create kv cache, warmup model) took 2.72 seconds (AsyncVLLMInferenceEngine pid=864077, ip=10.128.32.35) (EngineCore_DP0 pid=864319) WARNING 06-07 02:22:54 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 (AsyncVLLMInferenceEngine pid=864077, ip=10.128.32.35) (EngineCore_DP0 pid=864319) INFO 06-07 02:22:54 [vllm.py:690] Asynchronous scheduling is enabled. (AsyncVLLMInferenceEngine pid=864077, ip=10.128.32.35) (EngineCore_DP0 pid=864319) WARNING 06-07 02:22:54 [vllm.py:735] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. (AsyncVLLMInferenceEngine pid=864077, ip=10.128.32.35) (EngineCore_DP0 pid=864319) INFO 06-07 02:22:54 [vllm.py:846] Cudagraph is disabled under eager mode (AsyncVLLMInferenceEngine pid=863950, ip=10.128.32.35) WARNING 06-07 02:22:54 [model.py:1350] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`. (RolloutCoordinator pid=987693, ip=10.128.32.37) [fd-monitor] Started monitoring (every 120s) (RolloutCoordinator pid=987693, ip=10.128.32.37) [fd-monitor] [02:22:56] OK: 46 / 131,072 FDs open (0.0% of soft limit, hard limit: 131,072) (RolloutCoordinator pid=987693, ip=10.128.32.37) [fd-monitor] [02:22:56] OK: RSS 0.78 GiB | node mem 390.4/858.0 GiB used (45.5%), avail 467.6 GiB (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) (EngineCore_DP0 pid=864313) INFO 06-07 02:22:50 [default_loader.py:293] Loading weights took 13.45 seconds [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) (EngineCore_DP0 pid=864313) INFO 06-07 02:22:50 [gpu_model_runner.py:4222] Model loading took 15.27 GiB memory and 14.715511 seconds [repeated 3x across cluster] (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) [rank-0]: Loading model from /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/checkpoints/global_step_28/policy/model_world_size_8_rank_0.pt (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) [rank-0]: Loading extra_state from /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/checkpoints/global_step_28/policy/extra_state_world_size_8_rank_0.pt (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) [rank-0]: Loading optim from /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/checkpoints/global_step_28/policy/optim_world_size_8_rank_0.pt (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) (EngineCore_DP0 pid=864324) INFO 06-07 02:22:53 [gpu_worker.py:373] Available KV cache memory: 49.32 GiB [repeated 2x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) (EngineCore_DP0 pid=864324) INFO 06-07 02:22:53 [kv_cache_utils.py:1307] GPU KV cache size: 359,104 tokens [repeated 2x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) (EngineCore_DP0 pid=864324) INFO 06-07 02:22:53 [kv_cache_utils.py:1312] Maximum concurrency for 32,768 tokens per request: 10.96x [repeated 2x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) (EngineCore_DP0 pid=864324) INFO 06-07 02:22:53 [kernel_warmup.py:44] Skipping FlashInfer autotune because it is disabled. [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) (EngineCore_DP0 pid=864324) INFO 06-07 02:22:53 [core.py:278] init engine (profile, create kv cache, warmup model) took 2.83 seconds [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) (EngineCore_DP0 pid=864313) WARNING 06-07 02:22:54 [serial_utils.py:57] Allowing insecure serialization using pickle due to VLLM_ALLOW_INSECURE_SERIALIZATION=1 [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) (EngineCore_DP0 pid=864313) INFO 06-07 02:22:54 [vllm.py:690] Asynchronous scheduling is enabled. [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) (EngineCore_DP0 pid=864313) WARNING 06-07 02:22:54 [vllm.py:735] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored. [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864079, ip=10.128.32.35) (EngineCore_DP0 pid=864313) INFO 06-07 02:22:54 [vllm.py:846] Cudagraph is disabled under eager mode [repeated 3x across cluster] (AsyncVLLMInferenceEngine pid=864078, ip=10.128.32.35) WARNING 06-07 02:22:54 [model.py:1350] Default vLLM sampling parameters have been overridden by the model's `generation_config.json`: `{'temperature': 0.6, 'top_k': 20, 'top_p': 0.95}`. If this is not intended, please relaunch vLLM instance with `--generation-config vllm`. [repeated 3x across cluster] (skyrl_entrypoint pid=294281) [fd-monitor] [02:23:02] OK: 102 / 131,072 FDs open (0.1% of soft limit, hard limit: 131,072) (skyrl_entrypoint pid=294281) [fd-monitor] [02:23:02] OK: RSS 1.64 GiB | node mem 233.1/858.0 GiB used (27.2%), avail 624.9 GiB (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) [rank-0]: Successfully loaded model state dict (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) [rank-0]: Successfully loaded optimizer state (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) [rank-0]: Successfully loaded scheduler state (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) [rank-0]: Checkpoint loaded successfully from /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/checkpoints/global_step_28/policy (FSDPPolicyWorkerBase pid=2662729, ip=10.128.32.43) INFO 06-07 02:23:18 [pynccl.py:178] pynccl trace buffer enabled: size=10000 dump_dir=/e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps flush_interval=0 s (FSDPPolicyWorkerBase pid=294462) INFO 06-07 02:23:19 [pynccl.py:178] pynccl trace buffer enabled: size=10000 dump_dir=/e/data1/datasets/playground/ot-baf/experiments/_nccl_dumps flush_interval=0 s [repeated 7x across cluster] Error executing job with overrides: ['+terminal_bench_config=terminal_bench', 'trainer.strategy=fsdp2', 'trainer.algorithm.advantage_estimator=rloo_n', 'trainer.algorithm.use_kl_loss=false', 'trainer.algorithm.kl_loss_coef=0.0', 'trainer.algorithm.eps_clip_low=0.2', 'trainer.algorithm.eps_clip_high=0.05', 'trainer.algorithm.loss_reduction=sequence_mean', 'trainer.epochs=2', 'trainer.max_steps=80', 'trainer.update_epochs_per_batch=1', 'trainer.train_batch_size=64', 'trainer.policy_mini_batch_size=64', 'trainer.eval_batch_size=64', 'trainer.micro_forward_batch_size_per_gpu=4', 'trainer.micro_train_batch_size_per_gpu=1', 'trainer.max_prompt_length=999999', 'trainer.eval_interval=999999', 'trainer.eval_before_train=false', 'trainer.ckpt_interval=2', 'trainer.resume_mode=latest', 'trainer.hf_save_interval=5', '++trainer.hf_hub_repo_id=laion/ablation-pymethods2test-seqmean-arm0', '++trainer.hf_hub_private=false', '++trainer.hf_hub_revision=main', '++trainer.enable_db_registration=false', 'trainer.project_name=OpenThoughts-Agent', 'trainer.log_level=INFO', 'trainer.tracker_commit_each_step=true', 'trainer.logger=console', 'trainer.run_name=ablation-pymethods2test-seqmean-arm0', 'trainer.ckpt_path=/e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/checkpoints', 'trainer.export_path=/e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/exports', 'trainer.policy.optimizer_config.lr=8e-6', 'trainer.policy.optimizer_config.weight_decay=0.0', 'trainer.policy.optimizer_config.adam_betas=[0.9,0.999]', 'trainer.policy.optimizer_config.max_grad_norm=0.9', 'trainer.policy.fsdp_config.cpu_offload=false', 'trainer.policy.fsdp_config.reshard_after_forward=true', 'trainer.policy.fsdp_config.fsdp_size=4', 'trainer.policy.model.path=/e/home/jusers/feuer1/jupiter/.cache/huggingface/hub/models--laion--GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k-fixthink/snapshots/0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', 'trainer.ref.fsdp_config.cpu_offload=false', 'trainer.ref.fsdp_config.reshard_after_forward=true', 'trainer.ref.fsdp_config.fsdp_size=4', 'trainer.placement.colocate_all=false', 'trainer.placement.policy_num_nodes=2', 'trainer.placement.ref_num_nodes=2', 'trainer.placement.policy_num_gpus_per_node=4', 'trainer.placement.ref_num_gpus_per_node=4', 'trainer.fully_async.max_staleness_steps=16', 'trainer.fully_async.num_parallel_generation_workers=338', 'generator.backend=vllm', 'generator.timeout_multiplier=1.0', 'generator.model_dtype=bfloat16', 'generator.inference_engine_tensor_parallel_size=1', 'generator.num_inference_engines=48', 'generator.n_samples_per_prompt=8', 'generator.eval_n_samples_per_prompt=8', 'generator.gpu_memory_utilization=0.75', 'generator.max_num_seqs=24', 'generator.max_num_batched_tokens=65536', 'generator.enable_prefix_caching=true', 'generator.enable_chunked_prefill=true', 'generator.run_engines_locally=true', 'generator.weight_sync_backend=nccl', 'generator.async_engine=true', 'generator.batched=false', 'generator.enable_http_endpoint=true', 'generator.enable_ray_prometheus_stats=false', 'generator.vllm_stats_interval=1', 'generator.append_eos_token_after_stop_str_in_multi_turn=true', 'generator.max_turns=999999', 'generator.sampling_params.max_generate_length=4096', 'generator.sampling_params.temperature=0.7', 'generator.sampling_params.top_p=0.95', 'generator.sampling_params.top_k=20', '++generator.engine_init_kwargs.max_model_len=32768', '++generator.engine_init_kwargs.custom_chat_template_chat_completion_path=chat_templates/qwen3_thinking_acc.jinja2', '++generator.engine_init_kwargs.served_model_name=0e3bff0c4e51f6b9ec0713b98b9eec36efb91cc6', 'data.train_data=["/e/scratch/jureap59/feuer1/tasks/exp_rpt_pymethods2test-large"]', 'data.val_data=[]', '+terminal_bench_config.trials_dir=/e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/trace_jobs', '+terminal_bench_config.harbor.name=terminus-2', '+terminal_bench_config.harbor.max_episodes=999999', '+terminal_bench_config.harbor.enable_summarize=false', '+terminal_bench_config.harbor.store_all_messages=true', '+terminal_bench_config.harbor.trajectory_config.raw_content=true', '+terminal_bench_config.harbor.enable_episode_logging=false', '+terminal_bench_config.harbor.record_terminal_session=false', '+terminal_bench_config.harbor.enable_pane_logging=false', '+terminal_bench_config.harbor.strict_json_parser=true', '+terminal_bench_config.harbor.interleaved_thinking=true', '+terminal_bench_config.harbor.extra_body.chat_template_kwargs.enable_thinking=true', '+terminal_bench_config.harbor.override_timeout_sec=900', '+terminal_bench_config.harbor.override_cpus=1', '+terminal_bench_config.harbor.override_memory_mb=2048', '+terminal_bench_config.harbor.override_storage_mb=2048', '+terminal_bench_config.harbor.auto_snapshot=true', '+terminal_bench_config.harbor.verifier_override_timeout_sec=120', '+terminal_bench_config.harbor.max_retries=3', '+terminal_bench_config.harbor.min_wait_sec=60.0', '+terminal_bench_config.harbor.max_wait_sec=600.0', '+terminal_bench_config.harbor.wait_multiplier=2.0', '+terminal_bench_config.harbor.exclude_exceptions=["VerifierTimeoutError","VerifierRuntimeError","RewardFileNotFoundError","RewardFileEmptyError","VerifierOutputParseError"]', '+terminal_bench_config.harbor.n_concurrent_trials=675', '+terminal_bench_config.harbor.log_level=INFO', '+terminal_bench_config.harbor.enable_reward_shaping=false', '+terminal_bench_config.harbor.enable_error_classification=true', '+terminal_bench_config.harbor.mask_exceptions=["DaytonaError","EnvironmentStartTimeoutError","NetworkError","ConnectionError","RewardFileNotFoundError","RewardFileEmptyError","AgentEnvironmentTimeoutError","ContextLengthExceededError"]', '+terminal_bench_config.harbor.default_error_treatment=zero', '+terminal_bench_config.harbor.passthrough_exceptions=["AgentTimeoutError"]', '+terminal_bench_config.harbor.zero_exceptions=[]', '+terminal_bench_config.model_info.max_input_tokens=32000', '+terminal_bench_config.model_info.max_output_tokens=4096', '+terminal_bench_config.archiving.enabled=false', '+terminal_bench_config.trace_upload.enabled=true', '+terminal_bench_config.trace_upload.repo_org=DCAgent', '+terminal_bench_config.trace_upload.episodes=last', '+terminal_bench_config.trace_upload.dataset_type=SFT', '+terminal_bench_config.trace_upload.cleanup=true'] Traceback (most recent call last): File "", line 198, in _run_module_as_main File "", line 88, in _run_code File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/examples/terminal_bench/entrypoints/main_tbench.py", line 142, in main() File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/main.py", line 94, in decorated_main _run_hydra( File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/_internal/utils.py", line 394, in _run_hydra _run_app( File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/_internal/utils.py", line 457, in _run_app run_and_report( File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/_internal/utils.py", line 223, in run_and_report raise ex File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/_internal/utils.py", line 220, in run_and_report return func() ^^^^^^ File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/_internal/utils.py", line 458, in lambda: hydra.run( ^^^^^^^^^^ File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/_internal/hydra.py", line 132, in run _ = ret.return_value ^^^^^^^^^^^^^^^^ File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/core/utils.py", line 260, in return_value raise self._return_value File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/hydra/core/utils.py", line 186, in run_job ret.return_value = task_function(task_cfg) ^^^^^^^^^^^^^^^^^^^^^^^ File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/examples/terminal_bench/entrypoints/main_tbench.py", line 132, in main ray.get(skyrl_entrypoint.remote(cfg)) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/auto_init_hook.py", line 22, in auto_init_wrapper return fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^ File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/client_mode_hook.py", line 104, in wrapper return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/worker.py", line 2967, in get values, debugger_breakpoint = worker.get_objects( ^^^^^^^^^^^^^^^^^^^ File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/worker.py", line 1015, in get_objects raise value.as_instanceof_cause() ray.exceptions.RayTaskError(RuntimeError): ray::skyrl_entrypoint() (pid=294281, ip=10.128.32.33) File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/examples/terminal_bench/entrypoints/main_tbench.py", line 105, in skyrl_entrypoint exp.run() File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/entrypoints/main_base.py", line 483, in run asyncio.run(trainer.train()) File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/asyncio/runners.py", line 195, in run return runner.run(main) ^^^^^^^^^^^^^^^^ File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/asyncio/runners.py", line 118, in run return self._loop.run_until_complete(task) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/asyncio/base_events.py", line 691, in run_until_complete return future.result() ^^^^^^^^^^^^^^^ File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/fully_async_trainer.py", line 491, in train await self._train_loop() File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/fully_async_trainer.py", line 545, in _train_loop self.init_weight_sync_state() File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/trainer.py", line 851, in init_weight_sync_state raise RuntimeError( RuntimeError: init_weight_sync_state failed at Ray boundary: RayTaskError(RuntimeError)(RuntimeError('tp_size() failed at Ray boundary: ActorDiedError(RayTaskError(\'__init__\', \'Traceback (most recent call last):\\n File "python/ray/_raylet.pyx", line 1722, in ray._raylet.execute_task\\n File "python/ray/_raylet.pyx", line 1659, in ray._raylet.execute_task.function_executor\\n File "python/ray/_raylet.pyx", line 4342, in ray._raylet.CoreWorker.run_async_func_or_coro_in_event_loop\\n File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/concurrent/futures/_base.py", line 449, in result\\n return self.__get_result()\\n ^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result\\n raise self._exception\\n File "python/ray/_raylet.pyx", line 4329, in async_func\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/async_compat.py", line 52, in wrapper\\n return func(*args, **kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/_private/function_manager.py", line 693, in actor_method_executor\\n return method(__ray_actor, *args, **kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/util/tracing/tracing_helper.py", line 461, in _resume_span\\n return method(self, *_args, **_kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 1139, in __init__\\n super().__init__(*args, **kwargs)\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 603, in __init__\\n self.llm = self._create_engine(*args, **kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/ray/util/tracing/tracing_helper.py", line 461, in _resume_span\\n return method(self, *_args, **_kwargs)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/SkyRL/skyrl-train/skyrl_train/inference_engines/vllm/vllm_engine.py", line 1216, in _create_engine\\n engine = vllm.AsyncLLMEngine.from_engine_args(engine_args, stat_loggers=stat_loggers)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/async_llm.py", line 251, in from_engine_args\\n return cls(\\n ^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/async_llm.py", line 148, in __init__\\n self.engine_core = EngineCoreClient.make_async_mp_client(\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 124, in make_async_mp_client\\n return AsyncMPClient(*client_args)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 835, in __init__\\n super().__init__(\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/core_client.py", line 490, in __init__\\n with launch_core_engines(vllm_config, executor_class, log_stats) as (\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File "/e/scratch/jureap59/feuer1/miniforge3/lib/python3.12/contextlib.py", line 144, in __exit__\\n next(self.gen)\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/utils.py", line 936, in launch_core_engines\\n wait_for_engine_startup(\\n File "/e/scratch/jureap59/feuer1/OpenThoughts-Agent/envs/rl/lib/python3.12/site-packages/vllm/v1/engine/utils.py", line 995, in wait_for_engine_startup\\n raise RuntimeError(\\nRuntimeError: Engine core initialization failed. See root cause above. Failed core proc(s): {}\\n\', RuntimeError(\'Engine core initialization failed. See root cause above. Failed core proc(s): {}\'), \'ray::AsyncVLLMInferenceEngine.__init__\', None, None))')) Stopping Ray cluster... Ray cluster stopped [RLJobRunner] Crash detected (exit!=0) — preserving Ray logs to /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0/ray_logs BEFORE trace upload (so a wall-clock kill can't lose crash evidence)... Collecting Ray logs from worker jpbo-041-34... Collecting Ray logs from worker jpbo-041-35... Collecting Ray logs from worker jpbo-041-36... Collecting Ray logs from worker jpbo-041-37... Collecting Ray logs from worker jpbo-041-38... Collecting Ray logs from worker jpbo-041-39... Collecting Ray logs from worker jpbo-041-40... Collecting Ray logs from worker jpbo-041-41... Collecting Ray logs from worker jpbo-041-42... Collecting Ray logs from worker jpbo-041-43... Collecting Ray logs from worker jpbo-041-44... Collecting Ray logs from worker jpbo-041-45... Collecting Ray logs from worker jpbo-041-46... [RLJobRunner] Crash-time Ray log preservation complete. [RLJobRunner] Launching trace upload (training exit code: 1): repo_id: DCAgent/ablation-pymethods2test-seqmean-arm0 job_dir: /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ablation-pymethods2test-seqmean-arm0 episodes: last log: /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/logs/ablation-pymethods2test-seqmean-arm0_trace_upload.log [RLJobRunner] Waiting for trace upload to complete... [RLJobRunner] Trace upload failed with exit code 1. Preserving Ray logs to /e/data1/datasets/playground/ot-baf/ablation-pymethods2test-seqmean-arm0/ray_logs/ Collecting Ray logs from worker jpbo-041-34... Collecting Ray logs from worker jpbo-041-35... Collecting Ray logs from worker jpbo-041-36... Collecting Ray logs from worker jpbo-041-37... Collecting Ray logs from worker jpbo-041-38... Collecting Ray logs from worker jpbo-041-39... Collecting Ray logs from worker jpbo-041-40... Collecting Ray logs from worker jpbo-041-41... Collecting Ray logs from worker jpbo-041-42... Collecting Ray logs from worker jpbo-041-43... Collecting Ray logs from worker jpbo-041-44... Collecting Ray logs from worker jpbo-041-45... Collecting Ray logs from worker jpbo-041-46... Ray log preservation complete