code: def enum(
      name,
      iterable: Sized = None,
      *,
      is_silent: bool = False,
      is_children_silent: bool = False,
      is_timed: bool = True,
      is_track: bool = False,
      is_not_in_loop: bool = False,
      context=None,
  ):
      """
      This creates a monitored enumerator.
  
      Arguments:
          name (str, optional): Name of the iterator
          iterable (Sized): The iterable
  
      Keyword Arguments:
          is_silent (bool, optional): Whether not to print time taken. Defaults to ``False``.
          is_timed (bool, optional): Whether to measure time. Default to ``True``.
          is_children_silent (bool, optional): Whether to make child sections silent.
              Defaults to ``True``.
          is_track (bool, optional): Whether to track the time.
              Defaults to ``False``.
          is_not_in_loop (bool, optional): Whether to forcefully track this outside :func:`loop`.
              Defaults to ``False``.
          context (optional): Reference to another section that will be used for monitoring the iteration.
      """
      if iterable is None:
          iterable = name
          name = "Enumerate"
  
      return _internal().enum(
          name,
          iterable,
          is_silent=is_silent,
          is_children_silent=is_children_silent,
          is_timed=is_timed,
          is_track=is_track,
          is_not_in_loop=is_not_in_loop,
          section=context,
      )
  
imports: import functools
  from typing import Iterable, Sized, Collection, Callable, Tuple, Any, Dict
  from typing import Union, Optional, overload
  from labml.internal.monitor import TimeSummary
  from labml.internal.monitor import monitor_singleton
label_desc: Use image node_id 4 for calling a global function with example usage: enum(name, iterable) and returns: _internal