class_docstr: A transform enables transforming the set of time series contained in a dataset.
docstr: Transforms the given items and returns the transformed ones.
  
  Args:
      items:  The items to transform.
  
  Returns:
      The transformed items.
docstr_tok: ["Transforms","the","given","items","and","returns","the","transformed","ones",".","Args",":","items",":","The","items","to","transform",".","Returns",":","The","transformed","items","."]
code: def __call__(self, items: List[Item]) -> List[Item]:
      """
      Transforms the given items and returns the transformed ones.
  
      Args:
          items:  The items to transform.
  
      Returns:
          The transformed items.
      """
  
file_path: gluonts/src/gluonts/nursery/few_shot_prediction/src/meta/datasets/preprocessing/transform.py
imports: from abc import ABC, abstractmethod
  import json
  from itertools import cycle
  from pathlib import Path
  from typing import List, Optional, Any, Dict
  from gluonts.dataset.field_names import FieldName
  from .filters import Filter
label_desc: Use image node_id 1 for calling the Transform obj's underlying member method code with example usage: obj.__call__(items) without return types