class_docstr: A Type wrapper for `numpy.random.Generator`.
  
  The reason this exists (and `Generic` doesn't suffice) is that
  `Generator` objects that would appear to be equal do not compare equal
  with the ``==`` operator.
  
  This `Type` also works with a ``dict`` derived from
  `Generator.__get_state__`, unless the ``strict`` argument to `Type.filter`
  is explicitly set to ``True``.
class_docstr_tok: ["A","Type","wrapper","for","`","numpy.random.Generator","`",".","The","reason","this","exists","(","and","`","Generic","`","does","n't","suffice",")","is","that","`","Generator","`","objects","that","would","appear","to","be","equal","do","not","compare","equal","with","the","``","==","``","operator",".","This","`","Type","`","also","works","with","a","``","dict","``","derived","from","`","Generator.__get_state__","`",",","unless","the","``","strict","``","argument","to","`","Type.filter","`","is","explicitly","set","to","``","True","``","."]
code: def __eq__(self, other):
      return type(self) == type(other)
  
imports: from typing import TypeVar
  import numpy
  import pytensor
  from pytensor.graph.type import Type
label_desc: Use image node_id 4 for calling the RandomGeneratorType obj's underlying member method code with example usage: obj.__eq__(other) and returns: unknown