code: def product_of_gaussians(mus, sigmas_squared):
      """Compute mu, sigma of product of gaussians.
  
      Args:
          mus (torch.Tensor): Means, with shape :math:`(N, M)`. M is the number
              of mean values.
          sigmas_squared (torch.Tensor): Variances, with shape :math:`(N, V)`. V
              is the number of variance values.
  
      Returns:
          torch.Tensor: Mu of product of gaussians, with shape :math:`(N, 1)`.
          torch.Tensor: Sigma of product of gaussians, with shape :math:`(N, 1)`.
  
      """
      sigmas_squared = torch.clamp(sigmas_squared, min=1e-7)
      sigma_squared = 1.0 / torch.sum(
          torch.reciprocal(sigmas_squared), dim=0
      )
      mu = sigma_squared * torch.sum(mus / sigmas_squared, dim=0)
      return mu, sigma_squared
  
imports: import copy
  import math
  import warnings
  import torch
  from torch import nn
  import torch.nn.functional
label_desc: Use image node_id 16 for calling a global function with example usage: product_of_gaussians(mus, sigmas_squared) and returns: mu,  sigma_squared