Zerocost4DL - Running 3D UNET on local GPU

Hello folks,

I was wondering if there are any tutorials on running google colab - 3D UNET of Zerocost4DL with my local GPU resources. Currently I have been using the server based GPUs offered by google Colab, but I would like to train/predict using my local GPU as it has more computing capabilties (higher CUDA cores). Any suggestions on how to do this would be very much appreciated!



Hi Praveen, it’s nice that you get these working!
Local runtime makes a lot of sense for 3D U-Net. The way forward would be to set up local runtime from Colab following this link:

For this you’ll need to have installed Python, CUDA Toolkit and cuDNN.
Create a conda environment:

You can use the requirements.txt from this notebook:

And follow the Colab’s info for local runtime. We’re also working on getting a guide written for this so watch our GitHub as well!

I hope this helps.



Great thanks Romain. I will have a go at this today. Great tool by the way!

Hi Romain,

I get an error when I tried to create a conda environment as suggested in the Github instructions. Do you mind help me with this?

Here is the error message:

ERROR: Could not find a version that satisfies the requirement astropy==4.2.1
ERROR: No matching distribution found for astropy==4.2.1

Ok, think I figured it out. Astropy 4.2.1 needs Python 3.7 or higher. So I just ran

conda create -n myzerocostenv python=3.7

instead of

conda create -n myzerocostenv python=3.6.9

and now it installed Astropy. I hope using Python 3.7 does not interfere with anything else.

I also get another error as we go down the requirement list. This time it is:

ERROR: Could not find a version that satisfies the requirement en-core-web-sm==2.2.5
ERROR: No matching distribution found for en-core-web-sm==2.2.5

What could be the issue here?

Hi Praveen,
We now have some simplified requirements.txt files, for 3D -U-Net, please use the one below:

This should solve your issues.