docstr: This is simply sum over all weigth's norm to calculate models performance
  :param arch:
  :param device: CPU or GPU
  :param batch_data:
  :param batch_labels:
  :return:
code: def evaluate(
      self,
      arch: nn.Module,
      device,
      batch_data: object,
      batch_labels: torch.Tensor,
      space_name: str,
  ) -> float:
      """
      This is simply sum over all weigth's norm to calculate models performance
      :param arch:
      :param device: CPU or GPU
      :param batch_data:
      :param batch_labels:
      :return:
      """
  
      pass
  
file_path: singa/examples/model_selection/TRAILS-Database-Native-Model-Selection/internal/ml/model_selection/src/eva_engine/phase1/vote.py
imports: from src.eva_engine.phase1.algo.alg_base import Evaluator
  from .utils.autograd_hacks import *
  from src.common.constant import Config
label_desc: Use image node_id 2 for calling the VoteEvaluator obj's underlying member method code with example usage: obj.evaluate(arch, device, batch_data, batch_labels, space_name) without return types