src/predict.py

import torch
from model import LinearModel

def predict(x_value):
    model = LinearModel()
    model.load_state_dict(torch.load("models/model.pt"))
    model.eval()

    x = torch.tensor([[x_value]], dtype=torch.float32)
    y = model(x)
    print(f"Input: {x_value} | Prediction: {y.item()}")
def actual(x):
    return 2 * x + 3
if __name__ == "__main__":
    predict(4.0)
    print(f"Actual: {actual(4.0)}")