code: def _log(metric, value):
      """AzureML log wrapper.
  
      Record list of int or float as a list metrics so that we can plot it from AzureML workspace portal.
      Otherwise, record as a single value of the metric.
      """
      if run is not None:
          if (
              isinstance(value, list)
              and len(value) > 0
              and isinstance(value[0], (int, float))
          ):
              run.log_list(metric, value)
          else:
              # Force cast to str since run.log will raise an error if the value is iterable.
              run.log(metric, str(value))
      print(metric, "=", value)
  
imports: import argparse
  import os
  import shutil
  import tensorflow
  from recommenders.utils.constants import DEFAULT_USER_COL, DEFAULT_ITEM_COL, DEFAULT_RATING_COL
  from recommenders.utils.notebook_utils import execute_notebook, read_notebook
label_desc: Use image node_id 1 for calling a global function with example usage: _log(metric, value) without return types