class_docstr: Multiplicative-weight strategy which samples representations adaptively.
code: def _select(self):
      logits = tf.math.log(self.weights / tf.reduce_sum(self.weights))
      return tf.random.categorical(tf.reshape(logits, [1, -1]), 1)[0][
          0
      ].numpy()
  
imports: import gin
  import tensorflow.compat.v2
label_desc: Use image node_id 2 for calling the MultiplicativeWeightStrategy obj's underlying member method code with example usage: obj._select() and returns: tf