- numpy - ./wheels/tensorfaux-0.0.1-py3-none-any.whl import numpy as np from tensorfaux.layers import Input, Dense, Tanh from tensorfaux.models import Sequential from tensorfaux.optimizers import SGD np.random.seed(42) # Data X = np.reshape([[0, 0], [0, 1], [1, 0], [1, 1]], (4, 2, 1)) Y = np.reshape([[0], [1], [1], [0]], (4, 1, 1)) # Instantiation model = Sequential([ Input(2), Dense(3), Tanh(), Dense(1), Tanh(), ]) model.compile(optimizer=SGD(learning_rate=0.01, batch_size=3)) # Training model.fit(X, Y, epochs=10000, verbose=True) # Prediction Y_pred = model.predict(X) for (y_true, y_pred) in zip(Y, Y_pred): print(f'Actual: {y_true}, Predicted: {y_pred}')