code: def add_jitter(input: Anysor, jitter_val: float = 1e-3) -> Anysor:
      r"""
      Adds jitter (i.e., a small diagonal component) to the matrix this
      LinearOperator represents.
      This is equivalent to calling :meth:`~linear_operator.operators.LinearOperator.add_diagonal`
      with a scalar tensor.
  
      :param input: The matrix (or batch of matrices) :math:`\mathbf A` (... x N x N).
      :param jitter_val: The diagonal component to add
      :return: :math:`\mathbf A + \alpha (\mathbf I)`, where :math:`\mathbf A` is the linear operator
          and :math:`\alpha` is :attr:`jitter_val`.
      """
      return linear_operator.add_jitter(
          input=input, jitter_val=jitter_val
      )
  
imports: from typing import Optional, Tuple, Union
  import linear_operator
  import torch
  from linear_operator import LinearOperator
  from torch import Tensor
  from .None import beta_features, distributions, kernels, lazy, likelihoods, means, metrics, mlls, models, optim, priors, settings, utils, variational
  from .functions import inv_matmul, log_normal_cdf, logdet, matmul
  from .lazy import cat, delazify, lazify
  from .mlls import ExactMarginalLogLikelihood
  from .module import Module
label_desc: Use image node_id 2 for calling a global function with example usage: add_jitter(input, jitter_val) and returns: linear_operator