{
  "run_id": "Rishichaitanya-Nalluri--zengrad-tensorflow-claude-haiku-5-5-1793173393682081595",
  "checker": {
    "claims": [
      {
        "claim": "The README Implementation section imports ZenGrad from zengrad_tensorflow and it performs a Keras optimizer update with the documented hyperparameters",
        "command": "Python API zengrad_tensorflow.ZenGrad",
        "evidence": ":InitializeLog() is called are written to STDERR\nI0000 00:00:1793173794.776307    3047 port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\nI0000 00:00:1793173794.788852    3047 cudart_stub.cc:31] Could not find cuda drivers on your machine, GPU will not be used.\nE0000 00:00:1793173796.187311    3047 cuda_platform.cc:52] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)",
        "expected": "updated weights [0.9981059513768245,2.003743288932412]",
        "input": "learning_rate=0.01, weight_decay=0.0001, momentum=0.9, epsilon=1e-8; weights=[1.0,2.0], gradient=[0.1,-0.2]",
        "kind": "claim",
        "outcome": "Real input produced the expected result: [0.9981059513768245, 2.003743288932412]",
        "returncode": 0,
        "source": "from zengrad_tensorflow import ZenGrad  # Import the ZenGrad optimizer",
        "source_checked": true,
        "source_file": "README.md",
        "verdict": "yes"
      }
    ],
    "cycle_checks": [
      {
        "claim": "Scheduled or looping main behavior",
        "command": "",
        "evidence": "Inspected README.md and the zengrad_tensorflow package (__init__.py, zengrad_tensorflow.py) and setup.py. ZenGrad is an optimizer class with no cron, loop, webhook, scheduler, --once or --now trigger, so there is no product cycle to run.",
        "expected": "identify the product trigger",
        "input": "source inspection",
        "kind": "cycle",
        "outcome": "Inspected README.md and the zengrad_tensorflow package (__init__.py, zengrad_tensorflow.py) and setup.py. ZenGrad is an optimizer class with no cron, loop, webhook, scheduler, --once or --now trigger, so there is no product cycle to run.",
        "source": "repository entry points",
        "verdict": "yes"
      }
    ],
    "details": {
      "kind": "python_api",
      "needs_browser": false,
      "needs_credentials": false,
      "python_example": {
        "actual": [
          0.9981059514686015,
          2.003743288752119
        ],
        "source_file": "<guest-path>",
        "weights_before": [
          1.0,
          2.0
        ]
      },
      "returncode": 0,
      "scope": "product operation",
      "stderr": "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\nI0000 00:00:1793173782.205580    3039 port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\nI0000 00:00:1793173782.209662    3039 cudart_stub.cc:31] Could not find cuda drivers on your machine, GPU will not be used.\nI0000 00:00:1793173782.264568    3039 cpu_feature_guard.cc:227] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\nTo enable the following instructions: AVX2 AVX512F AVX512_VNNI AVX512_BF16 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\nWARNING: All log messages before absl::InitializeLog() is called are written to STDERR\nI0000 00:00:1793173787.415407    3039 port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\nI0000 00:00:1\n[excerpt truncated]",
      "stdout": "{\"actual\": [0.9981059514686015, 2.003743288752119], \"source_file\": \"<guest-path>\", \"weights_before\": [1.0, 2.0]}",
      "working": true
    },
    "evidence_strength": "readme_checked",
    "example_checks": [],
    "status": "PASS"
  },
  "diagnosis": null
}