a3_model.py

import os
import sys
import argparse
import numpy as np
import pandas as pd
import torch
from torch import nn
from torch import optim
# Whatever other imports you need

# You can implement classes and helper functions here too.

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Train and test a model on features.")
    parser.add_argument("featurefile", type=str, help="The file containing the table of instances and features.")
    # Add options here for part 3 -- hidden layer and nonlinearity,
    # and any other options you may think you want/need.  Document
    # everything.
    
    args = parser.parse_args()

    print("Reading {}...".format(args.featurefile))

    # implement everything you need here