class_docstr: The most basic inner structure of the Stochastic Gradient Trees that carries information
  about the gradient and hessian of a given observation.
code: def __init__(
      self,
      gradient: float = 0.0,
      hessian: float = 0.0,
      *,
      grad_hess=None,
  ):
      if grad_hess:
          self.gradient = grad_hess.gradient
          self.hessian = grad_hess.hessian
      else:
          self.gradient = gradient
          self.hessian = hessian
  
imports: from __future__ import annotations
  import collections
  import copy
  import dataclasses
  import functools
  import math
  import sys
  import typing
  from river.base.typing import FeatureName
  from river.stats import Cov, Var
label_desc: Use image node_id 1 to create a new GradHess object  with example: obj = GradHess(gradient, hessian)