code: def test_evaluate(self):
      config_file = [
          pathjoin(_data_dir, "config_fl_train.json"),
          pathjoin(_data_dir, "config_fl_evaluate.json"),
          pathjoin(_data_dir, "multi_gpu_evaluate.json"),
      ]
      # initialize algo
      algo = MonaiAlgo(
          bundle_root=_data_dir,
          config_train_filename=None,
          eval_workflow=ConfigWorkflow(
              config_file=config_file,
              workflow_type="train",
              logging_file=_logging_file,
          ),
          config_filters_filename=pathjoin(
              _data_dir, "config_fl_filters.json"
          ),
      )
      algo.initialize(extra={ExtraItems.CLIENT_NAME: "test_fl"})
      self.assertTrue(dist.get_rank() in (0, 1))
  
      # initialize model
      parser = ConfigParser()
      parser.read_config(
          [
              pathjoin(_data_dir, "config_fl_train.json"),
              pathjoin(_data_dir, "config_fl_evaluate.json"),
          ]
      )
      parser.parse()
      network = parser.get_parsed_content("network")
      data = ExchangeObject(weights=get_state_dict(network))
      # test evaluate
      metric_eo = algo.evaluate(data=data, extra={})
      self.assertIsInstance(metric_eo, ExchangeObject)
      metric = metric_eo.metrics
      self.assertIsInstance(metric["accuracy"], float)
  
file_path: MONAI/tests/test_fl_monai_algo_dist.py
imports: from __future__ import annotations
  import os
  import unittest
  from os.path import join
  import torch.distributed
  from monai.bundle import ConfigParser, ConfigWorkflow
  from monai.fl.client.monai_algo import MonaiAlgo
  from monai.fl.utils.constants import ExtraItems
  from monai.fl.utils.exchange_object import ExchangeObject
  from monai.networks import get_state_dict
  from tests.utils import DistCall, DistTestCase, SkipIfBeforePyTorchVersion, SkipIfNoModule, skip_if_no_cuda
label_desc: Use image node_id 2 for calling the TestFLMonaiAlgo obj's underlying member method code with example usage: obj.test_evaluate() without return types