class_docstr: Convert encodings stored in the pickle file to encoding and mask.
  Transform the pad and resize the embedding to match the generator config.
code: def __init__(
      self,
      encoding_lengths: List[int],
      encoding_keys: List[str],
      out_keys: Optional[List[str]] = None,
  ):
      assert len(encoding_keys) == len(encoding_lengths)
      self.encoding_lengths = encoding_lengths
      self.encoding_keys = encoding_keys
      self.out_keys = (
          out_keys if out_keys is not None else encoding_keys
      )
  
imports: from typing import List, Optional
  import torch
  from nemo.utils import logging
label_desc: Use image node_id 1 to create a new PickleTransform object  with example: obj = PickleTransform(encoding_lengths, encoding_keys, out_keys)