code: def setup_functions(self):
      def build_covariance_from_scaling_rotation(
          scaling, scaling_modifier, rotation
      ):
          L = build_scaling_rotation(
              scaling_modifier * scaling, rotation
          )
          actual_covariance = L @ L.transpose(1, 2)
          symm = strip_symmetric(actual_covariance)
          return symm
  
      self.scaling_activation = torch.exp
      self.scaling_inverse_activation = torch.log
  
      self.covariance_activation = (
          build_covariance_from_scaling_rotation
      )
  
      self.opacity_activation = torch.sigmoid
      self.inverse_opacity_activation = inverse_sigmoid
  
      self.rotation_activation = torch.nn.functional.normalize
  
imports: import torch
  import numpy
  from utils.general_utils import inverse_sigmoid, get_expon_lr_func, build_rotation
  from torch import nn
  import os
  from utils.system_utils import mkdir_p
  from plyfile import PlyData, PlyElement
  from utils.sh_utils import RGB2SH
  from simple_knn._C import distCUDA2
  from utils.graphics_utils import BasicPointCloud
  from utils.general_utils import strip_symmetric, build_scaling_rotation
label_desc: Use image node_id 1 for calling the GaussianModel obj's underlying member method code with example usage: obj.setup_functions() and returns: symm