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: Encodes a string. It will append a start token <s> (id=self.start_idx) and an end token </s>
  (id=self.end_idx).
  
  Args:
      s: The string to encode.
      pad_to: If not zero, pad by appending self.pad_idx until string is of length `pad_to`.
          Defaults to 0.
  
  Returns:
      The encoded LongTensor of indices.
docstr_tok: ["Encodes","a","string",".","It","will","append","a","start","token","<","s",">","(","id=self.start_idx",")","and","an","end","token","<","\/s",">","(","id=self.end_idx",")",".","Args",":","s",":","The","string","to","encode",".","pad_to",":","If","not","zero",",","pad","by","appending","self.pad_idx","until","string","is","of","length","`","pad_to","`",".","Defaults","to","0",".","Returns",":","The","encoded","LongTensor","of","indices","."]
code: def forward(self, s: str, pad_to=0) -> torch.LongTensor:
      """
      Encodes a string. It will append a start token <s> (id=self.start_idx) and an end token </s>
      (id=self.end_idx).
  
      Args:
          s: The string to encode.
          pad_to: If not zero, pad by appending self.pad_idx until string is of length `pad_to`.
              Defaults to 0.
  
      Returns:
          The encoded LongTensor of indices.
      """
      encoded = s.encode()
      n_pad = pad_to - len(encoded) if pad_to > len(encoded) else 0
      return torch.LongTensor(
          [self.start_idx]
          + [c for c in encoded]  # noqa
          + [self.end_idx]
          + [self.pad_idx for _ in range(n_pad)]
      )
  
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 2 for calling the CharByteEncoder obj's underlying member method code with example usage: obj.forward(s, pad_to) and returns: torch