class_docstr: Abstract class which defines an evaluator config.
class_docstr_tok: ["Abstract","class","which","defines","an","evaluator","config","."]
docstr: :return: the cadence at which we are having our model produce new predictions. Defaults to the retraining
      frequency if not explicitly provided.
docstr_tok: [":","return",":","the","cadence","at","which","we","are","having","our","model","produce","new","predictions",".","Defaults","to","the","retraining","frequency","if","not","explicitly","provided","."]
code: def cadence(self) -> Union[pd.Timedelta, pd.DateOffset]:
      """
      :return: the cadence at which we are having our model produce new predictions. Defaults to the retraining
          frequency if not explicitly provided.
      """
      if self._cadence is None:
          return self.retrain_freq
      return self._cadence
  
imports: from abc import abstractmethod
  from typing import Any, List, Tuple, Union
  import numpy
  import pandas
  from tqdm import tqdm
  from merlion.models.base import ModelBase
  from merlion.models.forecast.base import ForecasterBase
  from merlion.utils.misc import AutodocABCMeta
  from merlion.utils.resample import granularity_str_to_seconds, to_offset
  from merlion.utils.time_series import TimeSeries
label_desc: Use image node_id 6 for calling the EvaluatorConfig obj's underlying member method code with example usage: obj.cadence() and returns: self, self