class_docstr: A class representing probability distributions.
class_docstr_tok: ["A","class","representing","probability","distributions","."]
docstr: Number of event dimensions, i.e., length of the `event_shape` tuple.
  
  This is `0` for distributions over scalars, `1` over vectors,
  `2` over matrices, and so on.
docstr_tok: ["Number","of","event","dimensions",",","i.e.",",","length","of","the","`","event_shape","`","tuple",".","This","is","`","0","`","for","distributions","over","scalars",",","`","1","`","over","vectors",",","`","2","`","over","matrices",",","and","so","on","."]
code: def event_dim(self) -> int:
      r"""
      Number of event dimensions, i.e., length of the `event_shape` tuple.
  
      This is `0` for distributions over scalars, `1` over vectors,
      `2` over matrices, and so on.
      """
      raise NotImplementedError()
  
imports: from typing import cast, Any, List, Optional, Tuple
  import mxnet
  import numpy
  from mxnet import autograd
  from gluonts.mx import Tensor
label_desc: Use image node_id 9 for calling the Distribution obj's underlying member method code with example usage: obj.event_dim() without return types