首先,确认你安装的DGL版本是否支持CUDA。你可以访问DGL的官方GitHub仓库或官方文档来查找支持CUDA的版本信息。 使用pip或conda等包管理工具安装DGL的CUDA版本。例如,使用pip安装可以执行以下命令(具体版本号需根据实际情况替换): bash pip install dgl-cuXX 其中XX代表CUDA的版本号,如110表示CUDA
https://www.dgl.ai/pages/start.html,选择指定版本进行安装即可,如果在安装后,访问cuda时出现以下错误 /opt/dgl/src/runtime/c_runtime_api.cc:88: Check failed: allow_missing: Device API gpu is not enabled. Please install the cuda version of dgl. 可以降低安装的dgl的cuda版本,如果11.0出现错误,就...
This error may be caused by this function in models.py line 82: I have no idea to fix it. Could you try installing one of the GPU versions: conda install -c dglteam dgl-cuda10.0 Or pip install dgl-cu100 You may need to change 10.0 or 100 to match the CUDA version you have. When...
Hi,@HaleYan, it seems to be the problem of dgl, and you are expected to install the cuda version of dgl according to your environment by referring to thislink. Author Assignees No one assigned Labels None yet Projects None yet Milestone ...
CUDA Device Query (Runtime API) version (CUDART static linking) cudaGetDeviceCount returned 100 -> no CUDA-capable device is detected Result = FAIL (tf3.8) C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\extras\demo_suite>bandwidthTest.exe ...
I am not used to .deb and apt, but have experienced similar ‘API mismatch’ on openSUSE rpm repositories. Looks like previous installations are not cleaned up properly and/or a repository mismatch is in place. Recommendation: check /usr/local/ for /usr/local...
CUDA Device Query (Runtime API) version (CUDART static linking) cudaGetDeviceCount returned 38 -> no CUDA-capable device is detected Result = FAIL What could be wrong with this? Thanks Reply
"Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False" 错误提示表明您的代码尝试将一个在 CUDA 设备上训练好的模型加载到不支持 CUDA 的设备上,或者是将其加载到 CPU 上。要解决这个问题,您应该仔细检查 CUDA 和 PyTorch 的安装,并确保正确配置了系统。检查 GPU 驱动...
CUDA DEVICE API supported by HIP1. Device Functions CUDA A D R HIP A D R E _Pow_int __all __all 1.6.0 __any __any 1.6.0 __assert_fail __assert_fail 1.9.0 __assertfail __assertfail 1.9.0 __ballot __ballot 1.6.0...
CUDA Device Query (Runtime API) version (CUDART static linking) cudaGetDeviceCount returned 100 -> no CUDA-capable device is detected Result = FAIL System Information lspci | grep -i nvidiareturns: 04:00.0 VGA compatible controller: NVIDIA Corporation GA106 [GeForce RTX 3060 Lite Hash R...