class_docstr: Class to construct a distribution given the output of a network.
docstr: Number of event dimensions, i.e., length of the `event_shape` tuple,
  of the distributions that this object constructs.
docstr_tok: ["Number","of","event","dimensions",",","i.e.",",","length","of","the","`","event_shape","`","tuple",",","of","the","distributions","that","this","object","constructs","."]
code: def event_dim(self) -> int:
      r"""
      Number of event dimensions, i.e., length of the `event_shape` tuple,
      of the distributions that this object constructs.
      """
      return len(self.event_shape)
  
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 4 for calling the DistributionOutput obj's underlying member method code with example usage: obj.event_dim() and returns: len