class_docstr: A type alias for empirical kernel functions accepting a `get` argument.
  
  A kernel function that produces an empirical kernel from a single
  instantiation of a neural network specified by its parameters.
  
  Equivalent to `EmpiricalKernelFn`, but accepts a `get` argument, which can be
  for example `get=("nngp", "ntk")`, to compute both kernels together.
class_docstr_tok: ["A","type","alias","for","empirical","kernel","functions","accepting","a","`","get","`","argument",".","A","kernel","function","that","produces","an","empirical","kernel","from","a","single","instantiation","of","a","neural","network","specified","by","its","parameters",".","Equivalent","to","`","EmpiricalKernelFn","`",",","but","accepts","a","`","get","`","argument",",","which","can","be","for","example","`","get=","(","``","nngp","''",",","``","ntk","''",")","`",",","to","compute","both","kernels","together","."]
code: def __call__(
      self,
      x1: NTTree[jnp.ndarray],
      x2: Optional[NTTree[jnp.ndarray]],
      get: Get,
      params: PyTree,
      **kwargs,
  ) -> NTTree[jnp.ndarray]:
      ...
  
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 EmpiricalGetKernelFn obj's underlying member method code with example usage: obj.__call__(x1, x2, get, params) without return types