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ggml_cuda_init: failed to initialize CUDA: (null) on Windows with CUDA 12.9

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評估

難度
4/5
預估耗時
3-5 天
新手友好度
35/100
Issue 類型
缺陷
描述清晰度
基本清楚
活躍度
停滯
技術堆疊
c, cmake, python

研究方向

這個 issue 涉及在使用 CUDA 12.9 的 Windows 上 CUDA 初始化失敗的問題。首先檢查建置記錄和 CMake 設定(GGML_CUDA 旗標)。檢查 llama.cpp 原始碼中的 ggml_cuda_init 函式,以了解 CUDA runtime 檢查。驗證 CUDA toolkit 的安裝、驅動程式相容性和環境變數。在函式庫外執行簡單的 CUDA 測試程式有助於隔離問題。

由索引模型根據 Issue 內容生成。

描述

System Information:

  • OS: Windows
  • GPU: NVIDIA GeForce RTX 5060 Ti
  • NVIDIA Driver Version: 577.00
  • CUDA Version (from nvidia-smi): 12.9
  • Python Version: 3.12
  • Visual Studio: Visual Studio 2019 with "Desktop development with C++" workload

Problem Description:
I am unable to get llama-cpp-python to use my GPU. When I run a script to load a model with n_gpu_layers=-1, I get the error ggml_cuda_init: failed to initialize CUDA: (null), and all layers are
loaded on the CPU.

Troubleshooting Steps Taken:

  1. Installed llama-cpp-python using the following command in the "x64 Native Tools Command Prompt for VS 2019" with a Python virtual environment activated:
    1 set CMAKE_ARGS="-DGGML_CUDA=on" && pip install --upgrade --force-reinstall llama-cpp-python --no-cache-dir
  2. Verified that the command completes successfully, but the resulting installation does not use the GPU.
  3. Tried using the deprecated LLAMA_CUBLAS flag, which resulted in a build error (as expected).
  4. Performed a full cleanup of the environment:
    • pip uninstall llama-cpp-python
    • pip cache purge
    • Manually deleted leftover ~* directories from site-packages.
  5. Reinstalled after the cleanup, but the problem persists.
  6. Installed PyTorch with CUDA 12.1 support (pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121) before reinstalling llama-cpp-python, but this did not
    resolve the issue.
  7. Confirmed that the correct Python interpreter and virtual environment are being used.
  8. The run_with_llama_cpp.py script being used is:
1     from llama_cpp import Llama
2 
3     llm = Llama(
4       model_path="models/mistral-7b-instruct-v0.2.Q4_K_M.gguf",
5       n_gpu_layers=-1,
6       n_ctx=4096,
7       verbose=True
8     )
9 

10 output = llm(
11 "AI is going to ",
12 max_tokens=32,
13 stop=["."],
14 echo=True
15 )
16
17 print(output)

Request:
Could you please provide any insights into why the CUDA initialization might be failing, or suggest any further diagnostic steps? I can provide the full verbose build log if needed.

主要語言
Python
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平均合併
3 小時 57 分鐘
30 天內合併 PR
4

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  • 沒有 Dockerfile 或 Docker Compose 檔案
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  • 閱讀貢獻指南

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  3. Fork 儲存庫,在一個分支上完成修改。
  4. 送出 Pull Request,並在描述裡引用這個 Issue 編號。

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