Error reporting during CUDA training:
solution:
used during operation:
CUDA_VISIBLE_DEVICES=-1 python train_single.py
[br] https://www.136.la/tech/show-629533.html
Read More:
- Tensorflow 2.1.0 error resolution: failed call to cuinit: CUDA_ ERROR_ NO_ DEVICE: no CUDA-capable device is detected
- Resolved failed call to cuinit: CUDA_ ERROR_ NO_ DEVICE
- Tensorflow error in Windows: failed call to cuinit: CUDA_ ERROR_ UNKNOWN
- RuntimeError: cuda runtime error (100) : no CUDA-capable device is detected at /opt/conda/conda-bld/
- To solve the problem of importerror when installing tensorflow: libcublas.so . 10.0, failed to load the native tensorflow runtime error
- FCOS No CUDA runtime is found, using CUDA_HOME=’/usr/local/cuda-10.0′
- Error: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version
- failed call to cuInit: CUDA_ERROR_UNKNOWN: unknown error
- [MMCV]RuntimeError: CUDA error: no kernel image is available for execution on the device
- CUDA error: device-side assert triggered
- RuntimeError: CUDA error: device-side assert triggered
- Ubuntu cannot access USB device, failed to create a proxy device for the USB device
- Linux error ttyname failed: inappropriate IOCTL for device solution
- tensorflow.python.framework.errors_impl.InternalError: Failed to create session.
- RuntimeError:cuda runtime error (11) : invalid argument at /pytorch/aten/src/THC/generic
- Tensorflow ValueError: Failed to convert a NumPy array to a Tensor
- CUDA Error： no kernel image is available for execution on device
- Solution to CUDA installation failure problem visual studio integration failed
- Using pip to install tensorflow: tensorflow — is not a supported wheel on this platform
- Failed to dlsym make_device: undefined symbol: make_device