| import numpy as np | |
| # SpTn-Model-only-1P | |
| # Exactly ONE trainable parameter | |
| w = np.array(0.0) | |
| x = np.array([1.0, 2.0, 3.0, 4.0]) | |
| y = np.array([2.0, 4.0, 6.0, 8.0]) | |
| lr = 0.01 | |
| for step in range(1000): | |
| prediction = w * x | |
| error = prediction - y | |
| loss = np.mean(error ** 2) | |
| gradient = np.mean(2 * error * x) | |
| w -= lr * gradient | |
| print("SpTn-Model-only-1P") | |
| print("Parameter:", w) | |
| print("Loss:", loss) | |
| print("Prediction:", w * x) | |