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 probability density/mass function evaluated at `value`.
docstr_tok: ["Returns","the","probability","density\/mass","function","evaluated","at","`","value","`","."]
code: def pdf(self, value):
      r"""
      Returns the probability density/mass function evaluated at `value`.
      """
      return np.exp(self.log_prob(value))
  
imports: from numbers import Number
  from .utils import cached_property
  from ....None import np
label_desc: Use image node_id 4 for calling the Distribution obj's underlying member method code with example usage: obj.pdf(value) and returns: np