title: TF 2.0 print tensor values
body: <p>I'm learning the newest release of Tensorflow (2.0) and I have tried to run a simple code to slice a matrix.
  Using the decorator @tf.function I made the following class:</p>
  
  <pre><code>class Data:
  def __init__(self):
      pass
  
  def back_to_zero(self, input):
      time = tf.slice(input, [0,0], [-1,1])
      new_time = time - time[0][0]
      return new_time
  
  @tf.function
  def load_data(self, inputs):
      new_x = self.back_to_zero(inputs)
      print(new_x)
  </code></pre>
  
  <p>So, when run the code using a numpy matrix, I can't retrieve the numbers.</p>
  
  <pre><code>time = np.linspace(0,10,20)
  magntiudes = np.random.normal(0,1,size=20)
  x = np.vstack([time, magntiudes]).T
  
  
  d = Data()
  d.load_data(x)
  </code></pre>
  
  <p>Output:</p>
  
  <pre><code>Tensor("sub:0", shape=(20, 1), dtype=float64)
  </code></pre>
  
  <p>I need to get this tensor in a numpy format, but TF 2.0 has not the class tf.Session to use run() or eval() methods.</p>
  
  <p>Thanks for any help that you can offer me!</p>