code: def create(metric, *args, **kwargs):
      
      if callable(metric):
          return CustomMetric(metric, *args, **kwargs)
      elif isinstance(metric, list):
          composite_metric = CompositeEvalMetric()
          for child_metric in metric:
              composite_metric.add(create(child_metric, *args, **kwargs))
          return composite_metric
  
      return _create(metric, *args, **kwargs)
docs: Creates evaluation metric from metric names or instances of EvalMetric
      or a custom metric function.
  
      Parameters
      ----------
      metric : str or callable
          Specifies the metric to create.
          This argument must be one of the below:
  
          - Name of a metric.
          - An instance of `EvalMetric`.
          - A list, each element of which is a metric or a metric name.
          - An evaluation function that computes custom metric for a given batch of
            labels and predictions.
      *args : list
          Additional arguments to metric constructor.
          Only used when metric is str.
      **kwargs : dict
          Additional arguments to metric constructor.
          Only used when metric is str
  
      Examples
      --------
      >>> def custom_metric(label, pred):
      ...     return np.mean(np.abs(label - pred))
      ...
      >>> metric1 = mx.metric.create('acc')
      >>> metric2 = mx.metric.create(custom_metric)
      >>> metric3 = mx.metric.create([metric1, metric2, 'rmse'])