class_docstr: This is a generalization of a categorical distribution.
  
  The support for the DiscreteValued distribution can be any real valued range,
  whereas the categorical distribution has support [0, n_categories - 1] or
  [1, n_categories]. This generalization allows us to take the mean of the
  distribution over its support.
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code: def _event_shape_tensor(self):
      return tf.shape(self._values)[:-1]
  
file_path: acme/acme/tf/networks/distributions.py
imports: from typing import Optional
  import tensorflow
  import tensorflow_probability
label_desc: Use image node_id 8 for calling the DiscreteValuedDistribution obj's underlying member method code with example usage: obj._event_shape_tensor() and returns: tf