def build_generator():
    model = tf.keras.Sequential()

    # Encoder
    model.add(layers.Conv2D(64, (3, 3), activation='relu', padding='same', input_shape=(64, 64, 1)))
    model.add(layers.Conv2D(128, (3, 3), activation='relu', strides=2, padding='same'))
    model.add(layers.Conv2D(256, (3, 3), activation='relu', strides=2, padding='same'))

    # Decoder
    model.add(layers.Conv2DTranspose(128, (3, 3), activation='relu', strides=2, padding='same'))
    model.add(layers.Conv2DTranspose(64, (3, 3), activation='relu', strides=2, padding='same'))
    model.add(layers.Conv2D(2, (3, 3), activation='tanh', padding='same'))  # Change from 3 to 2

    return model