class_docstr: A Monte Carlo interpretation of :class:`~funsor.integrate.Integrate`
  expressions. This falls back to the previous interpreter in other cases.
  
  :param rng_key:
class_docstr_tok: ["A","Monte","Carlo","interpretation","of",":","class",":","`","~funsor.integrate.Integrate","`","expressions",".","This","falls","back","to","the","previous","interpreter","in","other","cases",".",":","param","rng_key",":"]
code: def __init__(self, *, rng_key=None, **sample_inputs):
      super().__init__("monte_carlo")
      self.rng_key = rng_key
      self.sample_inputs = OrderedDict(sample_inputs)
  
imports: import functools
  from collections import OrderedDict
  from funsor.cnf import Contraction
  from funsor.delta import Delta
  from funsor.gaussian import Gaussian
  from funsor.integrate import Integrate
  from funsor.interpretations import StatefulInterpretation
  from funsor.tensor import Tensor
  from funsor.terms import Approximate, Funsor, Number, Subs, Unary
  from funsor.util import get_backend
  from .None import ops
label_desc: Use image node_id 1 to create a new MonteCarlo object from inherited base classes: StatefulInterpretation with example: obj = MonteCarlo()