code: def __call__(self, model: nn.Module, data_loader: DataLoader):
      with torch.no_grad():
          metric_list = []
          sample_num = 0
          for data_input, target in data_loader:
              metric_value = self.metric(model(data_input), target)
              if isinstance(metric_value, torch.Tensor):
                  metric_value = metric_value.numpy()
              metric_list.append(metric_value * data_input.shape[0])
              sample_num += data_input.shape[0]
          return np.sum(metric_list) / sample_num
  
file_path: BigDL/python/nano/src/bigdl/nano/utils/pytorch/metric.py
imports: from typing import Callable
  import torch
  from torch import nn
  from torch.utils.data import DataLoader
  import numpy
label_desc: Use image node_id 2 for calling the NanoMetric obj's underlying member method code with example usage: obj.__call__(model, data_loader) and returns: unknown