class_docstr: Abstract class which defines an evaluator config.
class_docstr_tok: ["Abstract","class","which","defines","an","evaluator","config","."]
docstr: :param train_window: the maximum duration of data we would like to train the model on. ``None`` means no limit.
  :param retrain_freq: the frequency at which we want to re-train the model. ``None`` means we only train the
      model once on the initial training data.
  :param cadence: the frequency at which we want to obtain predictions from the model.
      ``None`` means that we obtain a new prediction at the same frequency as the model's predictive horizon.
      ``0`` means that we obtain a new prediction at every timestamp.
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code: def __init__(
      self,
      train_window: float = None,
      retrain_freq: float = None,
      cadence: float = None,
  ):
      """
      :param train_window: the maximum duration of data we would like to train the model on. ``None`` means no limit.
      :param retrain_freq: the frequency at which we want to re-train the model. ``None`` means we only train the
          model once on the initial training data.
      :param cadence: the frequency at which we want to obtain predictions from the model.
          ``None`` means that we obtain a new prediction at the same frequency as the model's predictive horizon.
          ``0`` means that we obtain a new prediction at every timestamp.
      """
      self.train_window = train_window
      self.retrain_freq = retrain_freq
      self.cadence = 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 1 to create a new EvaluatorConfig object  with example: obj = EvaluatorConfig(train_window, retrain_freq, cadence)