Running in Local GPUs

[muammara]

Hi Everyone, and thanks Jermey for the the lovely course…

Thought of sharing the following with you:
I spent sometime searching on how to run the course in Local GPU (Quadro M1000M), and found the following article:
1- How to install fastai v1 on Windows 10

Things did not work, so I tested the following:

2- How to check your pytorch / keras is using the GPU?

I showed I don’t have GPU:

3- I replaced the MS windows driver with NVIDIA manually (automatic update did not work)

4- I repeated (2), the GPU showed up

5- Tried Resnet34 exercise and failed complaining about Memory, so I reduced batch size (bs=8), it took sometime but worked…

Feeling the need for speed, will try the cloud platform…

[muammara]

For the second day, I’m still running in the local machine and working on Fruits 360 datasets.
I searched a bit to see if I can do the task a bit faster in my laptop and feel good about the results if I use ResNet18. So I googled the difference, and while I did not expect impressive accuracy about ResNet18, result was not bad at all in this dataset:

However, with only 2GB of memory in my workstation, this is not sustainable
Waiting for the weekend to try the cloud option, but most likely going for SageMaker…