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      "stderr": "Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n",
      "stdout": "minisweagent: INFO: Results will be saved to                                    \n/operator-home/benchm\nark-runs/qualification-owner/single-gpu-swift27-r2-swe/work/mini-output         \nLogging to '/operator-home/benchmark-runs/qualification-owner/single-gpu-swift27-r2-swe/work/mini-output/minisweagent.log'\nminisweagent: INFO: Loading dataset princeton-nlp/SWE-Bench_Verified, split     \ntest...                                                                         \nminisweagent: INFO: Instance filter: 500 -> 5 instances                         \nminisweagent: INFO: Running on 5 instances...                                   \nminisweagent: INFO: Building agent config from specs:                           \n['/operator-home/benc\nhmark-harness-cache/mini-swe-agent/a83fcae82d2a08f0ee0c688f9d137b3566c097f8/src/\nminisweagent/config/benchmarks/swebench.yaml',                                  \n'/operator-home/bench\nmark-runs/qualification-owner/single-gpu-swift27-r2-swe/work/anvil-swe-config.ya\nml']                                                                            \nminisweagent.environment: DEBUG: Starting container with command:               \n/usr/bin/docker run -d --name minisweagent-REDACTED -w /testbed --platform      \nlinux/amd64 --network none --rm                                                 \ndocker.io/swebench/sweb.eval.x86_64.django_1776_django-13512:latest sleep 2h    \nminisweagent.environment: INFO: Started container minisweagent-REDACTED with ID \nREDACTED_CONTAINER_ID                \nminisweagent: INFO: Saved trajectory to                                         \n'/operator-home/bench\nmark-runs/qualification-owner/single-gpu-swift27-r2-swe/work/mini-output/django_\n_django-13512/django__django-13512.traj.json'                                   \nminisweagent.environment: DEBUG: Starting container with command:               \n/usr/bin/docker run -d --name minisweagent-REDACTED -w /testbed --platform      \nlinux/amd64 --network none --rm                                                 \ndocker.io/swebench/sweb.eval.x86_64.pydata_1776_xarray-4356:latest sleep 2h     \nminisweagent.environment: INFO: Started container minisweagent-REDACTED with ID \nREDACTED_CONTAINER_ID                \nminisweagent: INFO: Saved trajectory to                                         \n'/operator-home/bench\nmark-runs/qualification-owner/single-gpu-swift27-r2-swe/work/mini-output/pydata_\n_xarray-4356/pydata__xarray-4356.traj.json'                                     \nminisweagent.environment: DEBUG: Starting container with command:               \n/usr/bin/docker run -d --name minisweagent-REDACTED -w /testbed --platform      \nlinux/amd64 --network none --rm                                                 \ndocker.io/swebench/sweb.eval.x86_64.pylint-dev_1776_pylint-8898:latest sleep 2h \nminisweagent.environment: INFO: Started container minisweagent-REDACTED with ID \nREDACTED_CONTAINER_ID                \nminisweagent: INFO: Saved trajectory to                                         \n'/operator-home/bench\nmark-runs/qualification-owner/single-gpu-swift27-r2-swe/work/mini-output/pylint-\ndev__pylint-8898/pylint-dev__pylint-8898.traj.json'                             \nminisweagent.environment: DEBUG: Starting container with command:               \n/usr/bin/docker run -d --name minisweagent-REDACTED -w /testbed --platform      \nlinux/amd64 --network none --rm                                                 \ndocker.io/swebench/sweb.eval.x86_64.sphinx-doc_1776_sphinx-9658:latest sleep 2h \nminisweagent.environment: INFO: Started container minisweagent-REDACTED with ID \nREDACTED_CONTAINER_ID                \nminisweagent: INFO: Saved trajectory to                                         \n'/operator-home/bench\nmark-runs/qualification-owner/single-gpu-swift27-r2-swe/work/mini-output/sphinx-\ndoc__sphinx-9658/sphinx-doc__sphinx-9658.traj.json'                             \nminisweagent.environment: DEBUG: Starting container with command:               \n/usr/bin/docker run -d --name minisweagent-REDACTED -w /testbed --platform      \nlinux/amd64 --network none --rm                                                 \ndocker.io/swebench/sweb.eval.x86_64.sympy_1776_sympy-12096:latest sleep 2h      \nminisweagent.environment: INFO: Started container minisweagent-REDACTED with ID \nREDACTED_CONTAINER_ID                \nminisweagent: INFO: Saved trajectory to                                         \n'/operator-home/bench\nmark-runs/qualification-owner/single-gpu-swift27-r2-swe/work/mini-output/sympy__\nsympy-12096/sympy__sympy-12096.traj.json'                                       \n  Overall Progress ($0.00) \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 5/5 100% 0:58:08 eta: 0:00:00\n\u250f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2533\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2533\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2513\n\u2503 Exit Status    \u2503 Count \u2503 Most recent instances                               \u2503\n\u2521\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2547\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2547\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2529\n\u2502 Submitted      \u2502     4 \u2502 sympy__sympy-12096, pylint-dev__pylint-8898,        \u2502\n\u2502                \u2502       \u2502 pydata_...                                          \u2502\n\u2502 LimitsExceeded \u2502     1 \u2502 sphinx-doc__sphinx-9658                             \u2502\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518"
    },
    {
      "command": [
        "/operator-home/benchmark-harness-cache/swe-python-environments/0bc9301c810a0e8f810569f10c082a8a03cc81a7b87fbc0cdd868ce30c27ff93/bin/python",
        "-m",
        "swebench.harness.run_evaluation",
        "--dataset_name",
        "princeton-nlp/SWE-bench_Verified",
        "--split",
        "test",
        "--predictions_path",
        "/operator-home/benchmark-runs/qualification-owner/single-gpu-swift27-r2-swe/work/predictions.jsonl",
        "--max_workers",
        "1",
        "--run_id",
        "single-gpu-swift27-r2-swe",
        "--timeout",
        "1800",
        "--report_dir",
        "/operator-home/benchmark-runs/qualification-owner/single-gpu-swift27-r2-swe/work/official-grader",
        "--instance_ids",
        "sphinx-doc__sphinx-9658",
        "sympy__sympy-12096",
        "django__django-13512",
        "pydata__xarray-4356",
        "pylint-dev__pylint-8898"
      ],
      "duration_s": 81.838379,
      "failure_class": "test_failure",
      "name": "official_grader",
      "output_truncated": false,
      "returncode": 0,
      "status": "failed",
      "stderr": "<frozen runpy>:128: RuntimeWarning: 'swebench.harness.run_evaluation' found in sys.modules after import of package 'swebench.harness', but prior to execution of 'swebench.harness.run_evaluation'; this may result in unpredictable behaviour\n2026-09-26 07:01:53,134 - httpx - INFO - HTTP Request: HEAD https://huggingface.co/datasets/princeton-nlp/SWE-bench_Verified/resolve/main/README.md \"HTTP/1.1 307 Temporary Redirect\"\n2026-09-26 07:01:53,142 - httpx - INFO - HTTP Request: HEAD https://huggingface.co/api/resolve-cache/datasets/princeton-nlp/SWE-bench_Verified/c104f840cc67f8b6eec6f759ebc8b2693d585d4a/README.md?%2Fdatasets%2Fprinceton-nlp%2FSWE-bench_Verified%2Fresolve%2Fmain%2FREADME.md=&etag=%22f362a6ce9579a3ee1922e3402463feef139b7d00%22 \"HTTP/1.1 200 OK\"\n2026-09-26 07:01:53,245 - httpx - INFO - HTTP Request: HEAD https://huggingface.co/datasets/princeton-nlp/SWE-bench_Verified/resolve/c104f840cc67f8b6eec6f759ebc8b2693d585d4a/SWE-bench_Verified.py \"HTTP/1.1 404 Not Found\"\n2026-09-26 07:01:53,512 - httpx - INFO - HTTP Request: HEAD https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/princeton-nlp/SWE-bench_Verified/princeton-nlp/SWE-bench_Verified.py \"HTTP/1.1 404 Not Found\"\n2026-09-26 07:01:53,602 - httpx - INFO - HTTP Request: GET https://huggingface.co/api/datasets/princeton-nlp/SWE-bench_Verified/revision/c104f840cc67f8b6eec6f759ebc8b2693d585d4a \"HTTP/1.1 200 OK\"\n2026-09-26 07:01:53,687 - httpx - INFO - HTTP Request: HEAD https://huggingface.co/datasets/princeton-nlp/SWE-bench_Verified/resolve/c104f840cc67f8b6eec6f759ebc8b2693d585d4a/.huggingface.yaml \"HTTP/1.1 404 Not Found\"\n2026-09-26 07:01:53,803 - httpx - INFO - HTTP Request: GET https://datasets-server.huggingface.co/info?dataset=princeton-nlp/SWE-bench_Verified \"HTTP/1.1 200 OK\"\n2026-09-26 07:01:53,892 - httpx - INFO - HTTP Request: GET https://huggingface.co/api/datasets/princeton-nlp/SWE-bench_Verified/tree/c104f840cc67f8b6eec6f759ebc8b2693d585d4a/data?recursive=true&expand=false \"HTTP/1.1 200 OK\"\n2026-09-26 07:01:53,976 - httpx - INFO - HTTP Request: GET https://huggingface.co/api/datasets/princeton-nlp/SWE-bench_Verified/tree/c104f840cc67f8b6eec6f759ebc8b2693d585d4a?recursive=false&expand=false \"HTTP/1.1 200 OK\"\n2026-09-26 07:01:54,071 - httpx - INFO - HTTP Request: HEAD https://huggingface.co/datasets/princeton-nlp/SWE-bench_Verified/resolve/c104f840cc67f8b6eec6f759ebc8b2693d585d4a/dataset_infos.json \"HTTP/1.1 404 Not Found\"\n2026-09-26 07:01:54,193 - httpx - INFO - HTTP Request: HEAD https://huggingface.co/datasets/princeton-nlp/SWE-bench_Verified/resolve/main/README.md \"HTTP/1.1 307 Temporary Redirect\"\n2026-09-26 07:01:54,201 - httpx - INFO - HTTP Request: HEAD https://huggingface.co/api/resolve-cache/datasets/princeton-nlp/SWE-bench_Verified/c104f840cc67f8b6eec6f759ebc8b2693d585d4a/README.md?%2Fdatasets%2Fprinceton-nlp%2FSWE-bench_Verified%2Fresolve%2Fmain%2FREADME.md=&etag=%22f362a6ce9579a3ee1922e3402463feef139b7d00%22 \"HTTP/1.1 200 OK\"\n2026-09-26 07:01:54,283 - httpx - INFO - HTTP Request: HEAD https://huggingface.co/datasets/princeton-nlp/SWE-bench_Verified/resolve/c104f840cc67f8b6eec6f759ebc8b2693d585d4a/SWE-bench_Verified.py \"HTTP/1.1 404 Not Found\"\n2026-09-26 07:01:54,371 - httpx - INFO - HTTP Request: HEAD https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/princeton-nlp/SWE-bench_Verified/princeton-nlp/SWE-bench_Verified.py \"HTTP/1.1 404 Not Found\"\n2026-09-26 07:01:54,459 - httpx - INFO - HTTP Request: HEAD https://huggingface.co/datasets/princeton-nlp/SWE-bench_Verified/resolve/c104f840cc67f8b6eec6f759ebc8b2693d585d4a/.huggingface.yaml \"HTTP/1.1 404 Not Found\"\n2026-09-26 07:01:54,551 - httpx - INFO - HTTP Request: GET https://datasets-server.huggingface.co/info?dataset=princeton-nlp/SWE-bench_Verified \"HTTP/1.1 200 OK\"\n2026-09-26 07:01:54,639 - httpx - INFO - HTTP Request: HEAD https://huggingface.co/datasets/princeton-nlp/SWE-bench_Verified/resolve/c104f840cc67f8b6eec6f759ebc8b2693d585d4a/dataset_infos.json \"HTTP/1.1 404 Not Found\"\n\rEvaluation:   0%|          | 0/4 [00:00<?, ?it/s, error=0, \u2713=0, \u2716=0]\rEvaluation:   0%|          | 0/4 [00:18<?, ?it/s, \u2713=0, \u2716=1, error=0]\rEvaluation:  25%|\u2588\u2588\u258c       | 1/4 [00:18<00:54, 18.18s/it, \u2713=0, \u2716=1, error=0]\rEvaluation:  25%|\u2588\u2588\u258c       | 1/4 [00:39<00:54, 18.18s/it, \u2713=1, \u2716=1, error=0]\rEvaluation:  50%|\u2588\u2588\u2588\u2588\u2588     | 2/4 [00:39<00:40, 20.01s/it, \u2713=1, \u2716=1, error=0]\rEvaluation:  50%|\u2588\u2588\u2588\u2588\u2588     | 2/4 [00:58<00:40, 20.01s/it, \u2713=1, \u2716=2, error=0]\rEvaluation:  75%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258c  | 3/4 [00:58<00:19, 19.42s/it, \u2713=1, \u2716=2, error=0]\rEvaluation:  75%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258c  | 3/4 [01:15<00:19, 19.42s/it, \u2713=2, \u2716=2, error=0]\rEvaluation: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 4/4 [01:15<00:00, 18.50s/it, \u2713=2, \u2716=2, error=0]\rEvaluation: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 4/4 [01:15<00:00, 18.82s/it, \u2713=2, \u2716=2, error=0]\n",
      "stdout": "Found 4 existing instance images. Will reuse them.\nRunning 4 instances...\nAll instances run.\nCleaning cached images...\nRemoved 0 images.\nTotal instances: 5\nInstances submitted: 5\nInstances completed: 4\nInstances incomplete: 0\nInstances resolved: 2\nInstances unresolved: 2\nInstances with empty patches: 1\nInstances with errors: 0\nUnstopped containers: 0\nUnremoved images: 5\nReport written to openai__swift15-27b-nvfp4-327k-r2.single-gpu-swift27-r2-swe.json\n"
    }
  ],
  "state": "incomplete",
  "summary": {
    "attempted": 5,
    "graded": 4,
    "resolve_rate": 0.5,
    "resolved": 2
  },
  "task_container_network": "none"
}