Tensorflow 1.13 and Theano 1.0.4 Not Using GPU

Date: Jun 15, 2019
User: Pablo Vega Behar

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 requirements page mentions support only for CUDA 10.0. Anyone else run into this problem? Why is the lambda stack using ve…

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?

I created a virtual environment 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?

Related Thread: Why Lambda Stack Not Install Tensorflow-GPU

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.