code: def test_reduce_trainer_metrics_dict_ordered_dict():
      dict_dict_trainer_metrics = OrderedDict(
          [
              (
                  "category_5B6BF",
                  OrderedDict(
                      [
                          (
                              "loss",
                              [
                                  TrainerMetric(
                                      epoch=0, step=1, value=0.0
                                  )
                              ],
                          ),
                          (
                              "accuracy",
                              [
                                  TrainerMetric(
                                      epoch=0, step=1, value=1.0
                                  )
                              ],
                          ),
                      ]
                  ),
              ),
              (
                  "combined",
                  {"loss": [TrainerMetric(epoch=0, step=1, value=0.0)]},
              ),
          ]
      )
  
      result = metric_utils.reduce_trainer_metrics_dict(
          dict_dict_trainer_metrics
      )
  
      assert result == {
          "category_5B6BF": {"accuracy": [1.0], "loss": [0.0]},
          "combined": {"loss": [0.0]},
      }
  
file_path: ludwig/tests/ludwig/utils/test_metric_utils.py
imports: from collections import OrderedDict
  import torch
  from ludwig.utils import metric_utils
  from ludwig.utils.metric_utils import TrainerMetric
label_desc: Use image node_id 5 for calling a global function with example usage: test_reduce_trainer_metrics_dict_ordered_dict() without return types