docstr: Transform `global_ids` and store the results in `cache_ids`.
code: def transform(
      self, global_ids: TensorList, cache_ids: TensorList, time: int
  ):
      """
      Transform `global_ids` and store the results in `cache_ids`.
      """
      result = self._transformer.transform(
          global_ids.tensor_list, cache_ids.tensor_list, time
      )
      return result.success, result.ids_to_fetch
  
file_path: torchrec/contrib/dynamic_embedding/src/torchrec_dynamic_embedding/id_transformer.py
imports: import json
  import os
  import torch
  from .tensor_list import TensorList
label_desc: Use image node_id 2 for calling the IDTransformer obj's underlying member method code with example usage: obj.transform(global_ids, cache_ids, time) and returns: result,  result