{
  "id": "tensorflow/cudnn-status-not-initialized",
  "signature": "InternalError: cuDNN initialization failed: CUDNN_STATUS_NOT_INITIALIZED",
  "signature_zh": "InternalError: cuDNN 初始化失败: CUDNN_STATUS_NOT_INITIALIZED",
  "regex": "cuDNN initialization failed: CUDNN_STATUS_NOT_INITIALIZED",
  "domain": "tensorflow",
  "category": "gpu_error",
  "subcategory": null,
  "root_cause": "cuDNN library failed to initialize, often due to incompatible CUDA/cuDNN version or insufficient GPU memory for internal buffers.",
  "root_cause_type": "generic",
  "root_cause_zh": "cuDNN 库初始化失败，通常是由于 CUDA/cuDNN 版本不兼容或 GPU 内存不足导致内部缓冲区分配失败。",
  "versions": [
    {
      "version": "tensorflow 2.10.0",
      "introduced": null,
      "deprecated": null,
      "removed": null,
      "behavior_change": null,
      "status": "active"
    },
    {
      "version": "tensorflow 2.11.0",
      "introduced": null,
      "deprecated": null,
      "removed": null,
      "behavior_change": null,
      "status": "active"
    },
    {
      "version": "tensorflow 2.12.0",
      "introduced": null,
      "deprecated": null,
      "removed": null,
      "behavior_change": null,
      "status": "active"
    }
  ],
  "os_specific": {},
  "dead_ends": [
    {
      "action": "",
      "why_fails": "The issue is usually a system-level library mismatch, not a Python package problem.",
      "fail_rate": 0.9,
      "condition": "",
      "sources": []
    },
    {
      "action": "",
      "why_fails": "Memory growth does not help with cuDNN initialization; it only controls dynamic allocation.",
      "fail_rate": 0.95,
      "condition": "",
      "sources": []
    },
    {
      "action": "",
      "why_fails": "Older versions may have the same or worse cuDNN compatibility issues.",
      "fail_rate": 0.8,
      "condition": "",
      "sources": []
    }
  ],
  "workarounds": [
    {
      "action": "Check and align CUDA and cuDNN versions by running `nvidia-smi` and `cat /usr/include/cudnn_version.h | grep CUDNN_MAJOR -A 2`. Then install matching TensorFlow: `pip install tensorflow==2.12.0`.",
      "success_rate": 0.85,
      "how": "Check and align CUDA and cuDNN versions by running `nvidia-smi` and `cat /usr/include/cudnn_version.h | grep CUDNN_MAJOR -A 2`. Then install matching TensorFlow: `pip install tensorflow==2.12.0`.",
      "condition": "",
      "sources": []
    },
    {
      "action": "Set environment variable `export TF_CPP_MAX_VLOG_LEVEL=1` before running the script to get detailed cuDNN logs, then adjust library paths accordingly.",
      "success_rate": 0.7,
      "how": "Set environment variable `export TF_CPP_MAX_VLOG_LEVEL=1` before running the script to get detailed cuDNN logs, then adjust library paths accordingly.",
      "condition": "",
      "sources": []
    }
  ],
  "workarounds_zh": [
    "Check and align CUDA and cuDNN versions by running `nvidia-smi` and `cat /usr/include/cudnn_version.h | grep CUDNN_MAJOR -A 2`. Then install matching TensorFlow: `pip install tensorflow==2.12.0`.",
    "Set environment variable `export TF_CPP_MAX_VLOG_LEVEL=1` before running the script to get detailed cuDNN logs, then adjust library paths accordingly."
  ],
  "transition_graph": {
    "leads_to": [],
    "preceded_by": [],
    "frequently_confused_with": []
  },
  "official_doc_url": "https://www.tensorflow.org/install/gpu",
  "official_doc_section": null,
  "error_code": "CUDNN_INIT",
  "verification_tier": "ai_generated",
  "confidence": 0.85,
  "fix_success_rate": 0.75,
  "resolvable": "partial",
  "first_seen": "2023-06-15",
  "last_confirmed": "2024-06-01",
  "last_updated": "2024-06-01",
  "evidence_count": 1,
  "tags": [],
  "locale": "en",
  "aliases": []
}