python - How to install CUDA in Google Colab GPU's

Question

It seems that Google Colab GPU's doesn't come with CUDA Toolkit, how can I install CUDA in Google Colab GPU's. I am getting this error in installing mxnet in Google Colab.

Installing collected packages: mxnet
Successfully installed mxnet-1.2.0

ERROR: Incomplete installation for leveraging GPUs for computations. Please make sure you have CUDA installed and run the following line in your terminal and try again:

pip uninstall -y mxnet && pip install mxnet-cu90==1.1.0

Adjust 'cu90' depending on your CUDA version ('cu75' and 'cu80' are also available). You can also disable GPU usage altogether by invoking turicreate.config.set_num_gpus(0). An exception has occurred, use %tb to see the full traceback.

SystemExit: 1

Answer 1

Cuda is not showing on your notebook because you have not enabled GPU in Colab.

The Google Colab comes with both options GPU or without GPU. You can enable or disable GPU in runtime settings

Go to Menu > Runtime > Change runtime.

Change hardware acceleration to GPU.

To check if GPU is running or not, run the following command

!nvidia-smi

If the output is like the following image it means your GPU and cuda are working. You can see the CUDA version also.

After that to check if PyTorch is capable of using GPU, run the following code.

import torch
torch.cuda.is_available()
# Output would be True if Pytorch is using GPU otherwise it would be False.

To check if TensorFlow is capable of using GPU, run the following code.

import tensorflow as tf
tf.test.gpu_device_name()
# Standard output is '/device:GPU:0'