class_docstr: Chain multiple transformations together.
class_docstr_tok: ["Chain","multiple","transformations","together","."]
code: def __call__(
      self, data_it: Iterable[DataEntry], is_train: bool
  ) -> Iterable[DataEntry]:
      tmp = data_it
      for t in self.transformations:
          tmp = t(tmp, is_train)
      return tmp
  
imports: import abc
  from dataclasses import dataclass
  from typing import Callable, Iterable, Iterator, List
  from gluonts.core.component import equals, validated
  from gluonts.dataset.common import DataEntry, Dataset
  from gluonts.env import env
label_desc: Use image node_id 2 for calling the Chain obj's underlying member method code with example usage: obj.__call__(data_it, is_train) and returns: tmp