ERA2_Session5: Pytorch 101

Welcome to an introduction to Pytorch.

Let's look at a sample code for training the MNIST data for identifying digits.

Our code is split into three files:

1. S5.ipynb

This is the main notebook where the flow of the code is defined.

2. model.py

Here you can see the structure of the Neural Network used for training our model.

3. utils.py

All supplementary functionalities like data download, visualizations etc are persent in this file.

Running the code

To run the code, you can simply clone the repo and start with S5.ipynb. If you are using Google Colab, the way I have, make sure that the main notebook and supporting codes provided by model.py and utils.py are saved onto your Google Drive and follow the two steps:

1) Mount your Google Drive:

from google.colab import drive
drive.mount('/content/drive', force_remount=True)

2) Change directory to where the files are located:

import os
os.chdir('/content/drive/MyDrive/ERA_V2/')
print("Current Working Directory:", os.getcwd())

Now you are good to proceed to run the code. Happy Learning!