text: # encoding:utf-8
  
  # three layer neural VirtualMic
  import tensorflow as tf
  from tensorflow import keras
  import numpy as np
  
  # (60000, 28, 28)
  (x_train, y_train) = np.array([[[1, 1]],
                                 [[1, 0]],
                                 [[0, 1]],
                                 [[0, 0]]]), np.array([1, 0, 0, 0])
  print(x_train.shape)
  
  model = keras.Sequential()
  model.add(keras.layers.Dense(input_shape=(1, 2), units=1))
  model.add(keras.layers.Dense(1, activation=keras.activations.linear))
  
  model.compile(optimizer=keras.optimizers.SGD.__name__,
                loss=keras.losses.mean_squared_error.__name__,
                metrics=["accuracy"])
  model.fit(x_train, y_train, epochs=100)
  print(model.predict([[[0, 1]]]))
  model.summary()
  
  # model.evaluate(x_test, y_test, verbose=2)