title: How to get tensor value in Tensorflow 2.0?
body: <p>I try to create custom layer in Keras. This code I get from examples. How to get result of calculation this Layer?</p>
  
  <pre><code>  class Linear(keras.layers.Layer):
          def __init__(self, units=32):
              super(Linear, self).__init__()
              self.units = units
  
          def build(self, input_shape):
              self.w = self.add_weight(
                  shape=(input_shape[-1], self.units),
                  initializer="random_normal",
                  trainable=True,
              )
              self.b = self.add_weight(
                  shape=(self.units,), initializer="random_normal", trainable=True
              )
  
          def call(self, inputs):
              return tf.matmul(inputs, self.w) + self.b
  
  
      x = tf.ones((2, 2))
  
      # At instantiation, we don't know on what inputs this is going to get called
      linear_layer = Linear(32)
  
      # The layer's weights are created dynamically the first time the layer is called
      y = linear_layer(x)
  
      print(type(y))
      print(y)
  </code></pre>
  
  <p>Output is:</p>
  
  <pre><code>&lt;class 'tensorflow.python.framework.ops.Tensor'&gt;
  Tensor("linear_17/add:0", shape=(2, 32), dtype=float32)
  </code></pre>
  
  <p>I need to get values of Tensor y. How to get them? tf.Session not working because I use Tensorflow 2.2.0.</p>