Nov 15, 2019 · The full line reads: RuntimeError: cuda runtime error (100): no CUDA-capable device is detected at /opt/conda/conda-bld/pytorch_1570910687650/work/aten/src/THC/THCGeneral.cpp:50 I am using
Jun 05, 2021 · After checking the installation problem, I found that there was no problem and then restart the computer to run. import tensorflow as tf sess = tf.Session(config=tf.ConfigProto(log_device_placement=True)) This is the test code, you can check whether the GPU can run normally.
Calls that may return this value include cudaEventQuery and cudaStreamQuery (). cudaErrorInsufficientDriver. This indicates that the installed NVIDIA CUDA driver is older than the CUDA runtime library.
Two immediate temporary solutions: 1. Physically remove all GPU cards, except one - single card configuration. or. 2. Install old GPU driver. The version 419.67 is working for us. Reason: The issue is with the CUDA memory de-allocation function, that has stopped working properly with latest NVIDIA GPU drivers.
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