code: def __post_init__(self):
      super().__post_init__()
  
      self.base_path = self.base_path or os.path.join(
          ENCODINGS_BASE, self.name
      )
      self.full_encoder_path = os.path.join(
          self.base_path, self.encoder_path
      )
      self.full_bpe_path = os.path.join(self.base_path, self.bpe_path)
  
      # We don't load the full BPE data until needed
      # Initialize them to 'None' here to make the linter happy
      # Note: Do not move these to @dataclass fields. That will lead to enormous outputs,
      #       since the default dataclass __repr__ prints the values of all fields.
      self._token_str_to_idx = None
      self._token_idx_to_str = None
      self.byte_decoder = None
      self.byte_encoder = None
      self.bpe_ranks = None
  
      # Without this cache, performance is 5x slower
      self.bpe = lru_cache(maxsize=2**17)(self.bpe)
  
imports: import json
  import os.path
  from dataclasses import dataclass
  from functools import lru_cache
  from typing import ClassVar
  import blobfile
  import regex
  import torch
label_desc: Use image node_id 1 for calling the BPEEncoding obj's underlying member method code with example usage: obj.__post_init__() without return types