class_docstr: A type alias for Monte Carlo kernel functions.
  
  A kernel function that produces an estimate of an `AnalyticKernel`
  by monte carlo sampling given a `PRNGKey`.
class_docstr_tok: ["A","type","alias","for","Monte","Carlo","kernel","functions",".","A","kernel","function","that","produces","an","estimate","of","an","`","AnalyticKernel","`","by","monte","carlo","sampling","given","a","`","PRNGKey","`","."]
code: def __call__(
      self,
      x1: NTTree[jnp.ndarray],
      x2: Optional[NTTree[jnp.ndarray]],
      get: Get = None,
      **kwargs,
  ) -> Union[
      NTTree[jnp.ndarray], Generator[NTTree[jnp.ndarray], None, None]
  ]:
      ...
  
imports: from typing import Any, Generator, Optional, Protocol, Sequence, TYPE_CHECKING, TypeVar, Union
  import jax
  import jax.numpy
  from .kernel import Kernel
label_desc: Use image node_id 1 for calling the MonteCarloKernelFn obj's underlying member method code with example usage: obj.__call__(x1, x2, get) without return types