text: import os
  import tensorflow as tf
  import numpy as np
  from tensorflow import keras
  
  os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
  print(tf.__version__)
  
  xs = np.array([-1.0,  0.0, 1.0, 2.0, 3.0, 4.0], dtype=float)
  ys = np.array([-3.0, -1.0, 1.0, 3.0, 5.0, 7.0], dtype=float)
  
  model = tf.keras.Sequential([keras.layers.Dense(units=1, input_shape=[1])])
  model.compile(optimizer='sgd', loss='mean_squared_error')
  model.fit(xs, ys, epochs=500)
  print(model.predict([10.0]))
  
  