class_docstr: Accumulator which maintains summary statistics describing a forecasting
  algorithm's performance. Can be used to compute many different forecasting metrics.
code: def check_before_eval(self):
      # Make sure time series is univariate
      assert self.predict.dim == self.ground_truth.dim == 1
      # Make sure the timestamps of preds and targets are identical
      assert self.predict.time_stamps == self.ground_truth.time_stamps
  
imports: from enum import Enum
  from functools import partial
  from typing import List, Union, Tuple
  import warnings
  import numpy
  import pandas
  from merlion.evaluate.base import EvaluatorBase, EvaluatorConfig
  from merlion.models.forecast.base import ForecasterBase
  from merlion.utils import TimeSeries, UnivariateTimeSeries
  from merlion.utils.resample import to_offset
label_desc: Use image node_id 2 for calling the ForecastScoreAccumulator obj's underlying member method code with example usage: obj.check_before_eval() without return types