import tensorflow as tf
import numpy as np
x_data = np.array([[0, 0], [0, 1], [1, 0], [1, 1]], dtype=np.float32)
y_data = np.array([[0], [1], [1], [0]], dtype=np.float32)
model = tf.keras.Sequential([tf.keras.layers.Dense(8, input_dim=2, activation='relu'),tf.keras.layers.Dense(8, activation='relu'),tf.keras.layers.Dense(1, activation='sigmoid')])
model.compile(optimizer='adam', loss='binary_crossentropy',metrics=['accuracy'])
model.fit(x_data, y_data, epochs=1000, verbose=0)
predictions = model.predict(x_data)
rounded_predictions = np.round(predictions)
print("Predictions:", rounded_predictions)

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