docker run -itd --name guider -v ${PWD}:/mnt -p 10001:22 -p 10002:8080 --gpus all -e NVIDIA_DRIVER_CAPABILITIES=compute,utility -e NVIDIA_VISIBLE_DEVICES=all --privileged=true --shm-size 32G nvidia/cuda:10.2-cu
("ngpu", 1) == 0: device = "cpu" kwargs["batch_size"] = 1 kwargs["device"] = device ``` 而export-onnx.py里的tensor默认都是cpu, 导致 RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu 所以直接在加载model的时候指定...
Use 'device=cpu' or pass valid CUDA device(s) if available, i.e. 'device=0' or 'device=0,1,2,3' for Multi-GPU. torch.cuda.is_available(): False torch.cuda.device_count(): 0 os.environ['CUDA_VISIBLE_DEVICES']: None See https://pytorch.org/get-started/locally/ for up-to-...
optimizeboolFalseApplies optimization for mobile devices when exporting to TorchScript, potentially reducing model size and improvinginferenceperformance. Not compatible with NCNN format or CUDA devices. halfboolFalseEnables FP16 (half-precision) quantization, reducing model size and potentially speeding up...
type == "cpu", "--optimize not compatible with cuda devices, i.e. use --device cpu" # Input gs = int(max(model.stride)) # grid size (max stride) imgsz = [check_img_size(x, gs) for x in imgsz] # verify img_size are gs-multiples ch = next(model.parameters()).size...
raise AttributeError(name) from None AttributeError: Float8_e5m2 Hi, Could you share the below info with us first? >>> import torch >>> torch.cuda.is_available() >>> torch.__version__ >>> import torchvision >>> torchvision.__version__ Thanks....
then which location libnvinfer_plugin.so* lib should be available? either /usr/local/cuda-10.0/lib64 or /usr/lib/aarch64-linux-gnu/ ???sdeep038 2019 年11 月 8 日 06:34 49 Hi morgan, I have question. when libnvinfer_plugin.so* and libnvinfer.so* created? when we instal...
API version: 3.0 (OpenCL 3.0 CUDA) Device version: 3.0 (OpenCL 3.0 CUDA) Vendor name: NVIDIA Driver date: UNKNOWN Driver age: UNKNOWN Driver version: UNKNOWN Bandwidth: 302 GB / s Compute score: 2,267.24 Device name string: NVIDIA GeForce RTX 2080 Super with...
# devices: 2 Device 0 Name: Quadro P2000 Preferred: TRUE Power Envelope: DISCRETE Attachment: UNKNOWN # attached displays: 0 GPU accessible RAM: 4,294 MB VRAM: 4,294 MB Dedicated System RAM: 0 MB Shared System RAM: 0 MB API version: 1.2 (OpenCL 1.2 CUD...
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