code: def init_render_func(
      self, shadingMode, pos_pe, view_pe, fea_pe, featureC, device
  ):
      if shadingMode == "MLP_PE":
          self.renderModule = MLPRender_PE(
              self.app_dim, view_pe, pos_pe, featureC
          ).to(device)
      elif shadingMode == "MLP_Fea":
          self.renderModule = MLPRender_Fea(
              self.app_dim, view_pe, fea_pe, featureC
          ).to(device)
      elif shadingMode == "MLP":
          self.renderModule = MLPRender(
              self.app_dim, view_pe, featureC
          ).to(device)
      elif shadingMode == "SH":
          self.renderModule = SHRender
      elif shadingMode == "RGB":
          assert self.app_dim == 3
          self.renderModule = RGBRender
      else:
          print("Unrecognized shading module")
          exit()
      print("pos_pe", pos_pe, "view_pe", view_pe, "fea_pe", fea_pe)
      print(self.renderModule)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from .sh import eval_sh_bases
  import numpy
  import time
label_desc: Use image node_id 2 for calling the TensorBase obj's underlying member method code with example usage: obj.init_render_func(shadingMode, pos_pe, view_pe, fea_pe, featureC, device) without return types