class_docstr: Class to construct a distribution given the output of a network.
docstr: Shape of each individual event contemplated by the distributions
  that this object constructs.
docstr_tok: ["Shape","of","each","individual","event","contemplated","by","the","distributions","that","this","object","constructs","."]
code: def event_shape(self) -> Tuple:
      r"""
      Shape of each individual event contemplated by the distributions
      that this object constructs.
      """
      raise NotImplementedError()
  
imports: from typing import Callable, Dict, Optional, Tuple, Type
  import numpy
  from mxnet import gluon
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
  from .distribution import Distribution
  from .transformed_distribution import AffineTransformedDistribution
label_desc: Use image node_id 3 for calling the DistributionOutput obj's underlying member method code with example usage: obj.event_shape() without return types