code: def load_param(self, param):
      if param is None:
          return
  
      for i in range(self.layer_nums):
          self.layers[i].load_param(param["layer_%d" % i])
  
      if self.residual:
          for i, fc in enumerate(self.fcs):
              key = f"layer_{i}_fc_{fc.weight.size(0)}_{fc.weight.size(1)}"
              if key in param:
                  self.fcs[i] = param[key]
      if self.batch_normal:
          for i, bn in enumerate(self.bns):
              key = f"layer_{i}_fc_{bn.weight.size(0)}"
              if key in param:
                  self.bns[i] = param[key]
  
imports: import torch
  import typing
  import torch.nn
  import torch.nn.functional
  from .None import register_nas_space
  from .base import BaseSpace, map_nn
  from ...model import BaseAutoModel
  from .operation import act_map
  from ..utils import count_parameters, measure_latency
  from ..backend import *
  from operator import *
  from .operation import *
label_desc: Use image node_id 8 for calling the GraphNet obj's underlying member method code with example usage: obj.load_param(param) without return types