import numpy as np
from tensorflow.keras import Sequential, Input, layers, optimizers

x = np.array([[0, 0, 0], [0, 0, 1], [0, 1, 0], [1, 0, 0], [0, 1, 1], [1, 0, 1], [1, 1, 0], [1, 1, 1]])
y = np.array([0, 1, 1, 1, 0, 0, 0, 1])

model = Sequential([
    Input(shape=(3,)),
    layers.Dense(3, activation="tanh"),
    layers.Dense(1, activation="sigmoid"),
])

model.compile(optimizer=optimizers.Adam(learning_rate=0.05), loss="binary_crossentropy", metrics=["accuracy"])
model.fit(x, y, epochs=100)

loss, accuracy = model.evaluate(x, y)
print(f"Loss: {loss}")
print(f"Accuracy: {accuracy}")

prediction = model.predict(x)
for inp, pred in zip(x, prediction):
    print(inp, round(pred[0]))