class_docstr: Applies a set of data transformations individually to an input time series.
  Stacks all of the results into a multivariate time series.
class_docstr_tok: ["Applies","a","set","of","data","transformations","individually","to","an","input","time","series",".","Stacks","all","of","the","results","into","a","multivariate","time","series","."]
code: def train(self, time_series: TimeSeries):
      for f in self.transforms:
          f.train(time_series)
  
imports: from collections import OrderedDict
  import logging
  from typing import List
  from merlion.transform.base import TransformBase, InvertibleTransformBase, Identity
  from merlion.transform.factory import TransformFactory
  from merlion.utils import TimeSeries
label_desc: Use image node_id 4 for calling the TransformStack obj's underlying member method code with example usage: obj.train(time_series) without return types