class_docstr: This encoder takes a UTF-8 string and encodes its bytes into a Tensor. It can also
  perform the opposite operation to check a result.
  
  Examples:
  
  >>> encoder = CharByteEncoder()
  >>> t = encoder('Ślusàrski')  # returns tensor([256, 197, 154, 108, 117, 115, 195, 160, 114, 115, 107, 105, 257])
  >>> encoder.decode(t)  # returns "<s>Ślusàrski</s>"
docstr: The length of our encoder space. This is fixed to 256 (one byte) + 3 special chars
  (start, end, pad).
  
  Returns:
      259
docstr_tok: ["The","length","of","our","encoder","space",".","This","is","fixed","to","256","(","one","byte",")","+","3","special","chars","(","start",",","end",",","pad",")",".","Returns",":","259"]
code: def __len__(self):
      """
      The length of our encoder space. This is fixed to 256 (one byte) + 3 special chars
      (start, end, pad).
  
      Returns:
          259
      """
      return 259
  
imports: import argparse
  from collections import Counter
  from pathlib import Path
  from statistics import mean
  import torch
  import torch.nn
  from opacus import PrivacyEngine
  from opacus.layers import DPGRU, DPLSTM, DPRNN
  from torch.nn.utils.rnn import pad_sequence
  from torch.utils.data import DataLoader, Dataset
  from tqdm import tqdm
label_desc: Use image node_id 4 for calling the CharByteEncoder obj's underlying member method code with example usage: obj.__len__() and returns: int