In terms of advantages/disadvantages, which method should i use to access Google Drive files on Colab? Google describes 3 methods here in the section labeled "Google Drive" https://colab.research.google.com/notebooks/io.ipynb#scrollTo=c2W5A2px3doP They have 3 ways: 1.Using the native REST API;
2.Using a wrapper around the API such as PyDrive; or
3.Mounting your Google Drive in the runtime's virtual machine.
I tried the last one - Mounting ~ machine as it seems the least complex but I can't seem to be able to find documentation on how to read and download files to my google drive folders with multiple tensorflow runs easily.
Is number 3 more limited than doing it via PyDrive for large runs and if so how it is so?