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 __iadd__(self, other):
      self.gradient += other.gradient
      self.hessian += other.hessian
  
      return self
  
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 2 for calling the GradHess obj's underlying member method code with example usage: obj.__iadd__(other) and returns: self