import pandas as pd
import torch
import torch.nn as nn

df = pd.read_csv("./RegressionModels/AdvertisementPrediction/advertising.csv")

X = torch.tensor(df[["TV", "Radio", "Newspaper"]].values, dtype=torch.float32)
Y = torch.tensor(df["Sales"].values, dtype=torch.float32)

model = torch.nn.Sequential(
    torch.nn.Linear(3,1)
)

loss_fn = torch.nn.MSELoss()
optimizer = torch.optim.SGD(model.parameters(), lr=3e-5)

for epoch in range(2000):
    y_pred = model(X)
    loss = loss_fn(y_pred, Y)
    optimizer.zero_grad()
    loss.backward()
    optimizer.step()
    if epoch % 100 == 99:
        print(f'Epoch {epoch+1}, Loss: {loss.item():.2f}')