Tensorflow 1.13 and Theano 1.0.4 Not Using GPU

Issue Update

I uninstalled and reinstalled the lambda stack. It did install with CUDA 10.1 and TensorFlow 1.13. tensorflow.test.is_gpu_available still returns ‘False’ and the TensorFlow GPU reqs page mentions support only for CUDA 10.0.
Anyone else run into this problem? Why is the lambda stack using ve…

Observations on Compatibility

So apparently TF 1.13 does not work with CUDA 10.1. I’m guessing 10.1 is not the current lambda stack version. Does this mean I have another Ubuntu auto-update somewhere updating CUDA? If so, how can I find this?

Virtual Environment Testing

I created a virtualenv using the lambdastack. Using TensorFlow 1.13 and running: tf.test.is_gpu_available returns a stack that includes: “failed call to cuInit: CUDA_ERROR_UNKNOWN: unknown error” which is not terribly helpful. A similar check for Theano shows it’s not using the GPU. Any tips?

Additional Queries

Did you solve this issue? My models are also training on CPU, not GPU. TensorFlow does not recognize the GPU from Jupyter or console. I created an environment from lambda stack following the instructions in this forum. Pip list does show tensorflow-gpu in the virtual environment.