最后,重新编译并运行你的CUDA程序,检查是否还会出现“invalid device requested”错误。如果设备ID已经更正且CUDA安装无误,那么错误应该不再出现。 综上所述,解决“cuda unavailable, invalid device 1 requested”错误的关键在于确认CUDA的安装情况、系统中CUDA设备的数量以及代码中请求的设备ID是否有效。通过这些步骤,你...
注意,该报错同样可以是AssertionError: CUDA unavailable, invalid device0/1/2requested,取决于用的那个device编号的显卡。 大致看了一遍 RuntimeError: CUDA error: no kernel image is available for execution on the driver, when use pytorch 1.7 on linux with RTX 3090 · Issue #49161 · pytorch/pytorch...
pytorch bug解决:AssertionError: CUDA unavailable, invalid device 0 requested 注意,该报错同样可以是AssertionError: CUDA unavailable, invalid device0/1/2requested,取决于用的那个device编号的显卡。 大致看了一遍 RuntimeError: CUDA error: no kernel image is available for execution on the driver, when us...
1.6.0版本的torch不支持低版本的cuda 10.1 所以检测不到gpu,安装兼容10.1低版本cuda的对应torch版本1.6.0+cu101 pip install torch==1.6.0+cu101 torchvision==0.7.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html
The model runs in a container fine when using cpu. However, it does not run if i specify to use GPU. I get the following error: AssertionError: CUDA unavailable, invalid device 0 requested. It seems like docker is not able to get access to my GPU. If you can please tell me how I...
YOLOv5 🚀 v5.0-187-g6062319torch 1.8.1 CPU when manually select GPU python3 detect.py --source ./data/images/zidane.jpg --conf 0.5 --device 0 AssertionError: CUDA unavailable, invalid device 0 requested Kindly anyone help me find solution for this ...
pytorch bug解决:AssertionError: CUDA unavailable, invalid device 0 requested 不过跟上面bug的不同之处在于, torch.cuda.is_available()可能为True,却依然报该错。但跟上面解决方案一样,重装适配cuda,且版本对应的torch、torchvision就好了。 --- 2022/9/18日更新--- 今天发现容器中仍然报了这个错,但版本是对...
您忘记在软件包和版本号之间放置==标志.根据PyTorch installation page：
Tell the CUDA runtime that DeviceFlags is being set in cudaInitDevice call #define cudaInvalidDeviceId ((int)-2) Device id that represents an invalid device #define cudaIpcMemLazyEnablePeerAccess 0x01 Automatically enable peer access between remote devices as needed #define cudaMemAttach...
if device and not cpu_request: # if device requested other than 'cpu' os.environ['CUDA_VISIBLE_DEVICES'] = device # set environment variable assert torch.cuda.is_available(), 'CUDA unavailable, invalid device %s requested' % device # check availablity cuda = False if cpu_request else...