CUDA 10.1.243 + tensorflow-gpu 2.3.0rc0 (CUDA runtime error: device kernel image invalid))

Hi,

I have a python virtual environment (conda) where I’ve installed CUDA toolkit 10.1.243 and tensorflow-gpu 2.3.0rc0. My CUDA driver is 11.0.

In order to test if tensorflow was installed to GPU correctly, I ran a series of commands from within the venv:

tf.test.is_built_with_cuda()
True

tf.config.list_physical_devices(‘GPU’)
Found device 0 with properties:
pciBusID: 0000:01:00.0 name: Quadro M2000M computeCapability: 5.0
[PhysicalDevice(name=’/physical_device:GPU:0’, device_type=‘GPU’)]

python -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000,1000])))"
tensorflow.python.framework.errors_impl.InternalError: CUDA runtime implicit initialization on GPU:0 failed. Status: device kernel image is invalid

I am not sure how to troubleshoot this. I have a feeling that it is related to modifying the compilation such that tensorflow supports the compute capability of my device (5.0), but I am not sure how to proceed. Thank you!!

Hi @bpwilliams13

I don’t have more information but if you use tensorflow 2.2.0, it can work fine.
You can only get this issue on tensorflow-2.3.0.