class_docstr: Base class for distribution.
  
  Parameters
  ----------
  event_dim : int, default None
      Variable indicating the dimension of the distribution's support.
  validate_args : bool, default None
      Whether to validate the distribution parameters
docstr: Returns the log of the probability density/mass function evaluated at `value`.
docstr_tok: ["Returns","the","log","of","the","probability","density\/mass","function","evaluated","at","`","value","`","."]
code: def log_prob(self, value):
      r"""
      Returns the log of the probability density/mass function evaluated at `value`.
      """
      raise NotImplementedError()
  
imports: from numbers import Number
  from .utils import cached_property
  from ....None import np
label_desc: Use image node_id 3 for calling the Distribution obj's underlying member method code with example usage: obj.log_prob(value) without return types