# 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.