在使用函数'torch.cuda.is_available()‘时,返回一个false。我读到这意味着驱动程序配置不正确,但是我不知道如何解决这个问题。
如果你需要更多的信息,请告诉我。
几天来,我一直在努力想办法解决这个问题,有人能发现这个问题吗?
谢谢
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 511.23 Driver Version: 511.23 CUDA Version: 11.6 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Quadro T2000 WDDM | 00000000:01:00.0 Off | N/A |
| N/A 52C P8 5W / N/A | 0MiB / 4096MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
Collecting environment information...
PyTorch version: 1.12.0
Is debug build: False
CUDA used to build PyTorch: Could not collect
ROCM used to build PyTorch: N/A
OS: Microsoft Windows 10 Enterprise
GCC version: Could not collect
Clang version: Could not collect
CMake version: Could not collect
Libc version: N/A
Python version: 3.8.13 (default, Mar 28 2022, 06:59:08) [MSC v.1916 64 bit (AMD64)] (64-bit runtime)
Python platform: Windows-10-10.0.19042-SP0
Is CUDA available: False
CUDA runtime version: 11.6.55
GPU models and configuration: GPU 0: Quadro T2000
Nvidia driver version: 511.23
cuDNN version: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.6\bin\cudnn_ops_train64_8.dll
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
Versions of relevant libraries:
[pip3] numpy==1.22.3
[pip3] torch==1.12.0
[pip3] torchaudio==0.12.0
[pip3] torchvision==0.13.0
[conda] blas 1.0 mkl
[conda] cpuonly 2.0 0 pytorch
[conda] cudatoolkit 11.6.0 hc0ea762_10 conda-forge
[conda] mkl 2021.4.0 haa95532_640
[conda] mkl-service 2.4.0 py38h2bbff1b_0
[conda] mkl_fft 1.3.1 py38h277e83a_0
[conda] mkl_random 1.2.2 py38hf11a4ad_0
[conda] numpy 1.22.3 py38h7a0a035_0
[conda] numpy-base 1.22.3 py38hca35cd5_0
[conda] pytorch 1.12.0 py3.8_cpu_0 pytorch
[conda] pytorch-mutex 1.0 cpu pytorch
[conda] torch 1.12.0 pypi_0 pypi
[conda] torchaudio 0.12.0 pypi_0 pypi
[conda] torchvision 0.13.0 pypi_0 pypi发布于 2022-07-08 16:07:30
PyTorch不使用系统的CUDA库。当您使用pip或conda使用预编译二进制文件安装PyTorch时,它会随本地安装的指定版本的CUDA库的副本一起提供。事实上,您甚至不需要在您的系统上安装CUDA来使用PyTorch和CUDA支持。
有两种情况可能会导致您的问题。
要确定安装PyTorch时要使用的适当命令,可以在pytorch.org的"Install“部分中使用方便的小部件。只需选择适当的操作系统、包管理器和CUDA版本,然后运行推荐的命令。
https://stackoverflow.com/questions/72914058
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