




lowerCamelCase__				:     Optional[int]			       =							{
    'A': ('ABCDEFGHIJKLM', 'NOPQRSTUVWXYZ'),
    'B': ('ABCDEFGHIJKLM', 'NOPQRSTUVWXYZ'),
    'C': ('ABCDEFGHIJKLM', 'ZNOPQRSTUVWXY'),
    'D': ('ABCDEFGHIJKLM', 'ZNOPQRSTUVWXY'),
    'E': ('ABCDEFGHIJKLM', 'YZNOPQRSTUVWX'),
    'F': ('ABCDEFGHIJKLM', 'YZNOPQRSTUVWX'),
    'G': ('ABCDEFGHIJKLM', 'XYZNOPQRSTUVW'),
    'H': ('ABCDEFGHIJKLM', 'XYZNOPQRSTUVW'),
    'I': ('ABCDEFGHIJKLM', 'WXYZNOPQRSTUV'),
    'J': ('ABCDEFGHIJKLM', 'WXYZNOPQRSTUV'),
    'K': ('ABCDEFGHIJKLM', 'VWXYZNOPQRSTU'),
    'L': ('ABCDEFGHIJKLM', 'VWXYZNOPQRSTU'),
    'M': ('ABCDEFGHIJKLM', 'UVWXYZNOPQRST'),
    'N': ('ABCDEFGHIJKLM', 'UVWXYZNOPQRST'),
    'O': ('ABCDEFGHIJKLM', 'TUVWXYZNOPQRS'),
    'P': ('ABCDEFGHIJKLM', 'TUVWXYZNOPQRS'),
    'Q': ('ABCDEFGHIJKLM', 'STUVWXYZNOPQR'),
    'R': ('ABCDEFGHIJKLM', 'STUVWXYZNOPQR'),
    'S': ('ABCDEFGHIJKLM', 'RSTUVWXYZNOPQ'),
    'T': ('ABCDEFGHIJKLM', 'RSTUVWXYZNOPQ'),
    'U': ('ABCDEFGHIJKLM', 'QRSTUVWXYZNOP'),
    'V': ('ABCDEFGHIJKLM', 'QRSTUVWXYZNOP'),
    'W': ('ABCDEFGHIJKLM', 'PQRSTUVWXYZNO'),
    'X': ('ABCDEFGHIJKLM', 'PQRSTUVWXYZNO'),
    'Y': ('ABCDEFGHIJKLM', 'OPQRSTUVWXYZN'),
    'Z': ('ABCDEFGHIJKLM', 'OPQRSTUVWXYZN'),
}

def       UpperCAmelCase_							(   __UpperCAmelCase		:			str							)      ->				list[tuple[str, str]]:
      return [alphabet[char] for char in key.upper()]

def       UpperCAmelCase_							(   __UpperCAmelCase		:			str    ,    __UpperCAmelCase		:			str							)      ->				str:
      SCREAMING_SNAKE_CASE_					=    ''
      SCREAMING_SNAKE_CASE_					=    0
      SCREAMING_SNAKE_CASE_					=    generate_table(__UpperCAmelCase							)
      for char in words.upper():
            cipher += get_opponent(table[count]    ,    __UpperCAmelCase							)
            SCREAMING_SNAKE_CASE_					=    (count + 1) % len(__UpperCAmelCase							)
      return cipher

def       UpperCAmelCase_							(   __UpperCAmelCase		:			str    ,    __UpperCAmelCase		:			str							)      ->				str:
      return encrypt(__UpperCAmelCase    ,    __UpperCAmelCase							)

def       UpperCAmelCase_							(   __UpperCAmelCase		:			tuple[str, str]    ,    __UpperCAmelCase		:			str							)      ->				tuple[int, int]:
      SCREAMING_SNAKE_CASE_					=    0 if char in table[0] else 1
      SCREAMING_SNAKE_CASE_					=    table[row].index(__UpperCAmelCase							)
      return row, col

def       UpperCAmelCase_							(   __UpperCAmelCase		:			tuple[str, str]    ,    __UpperCAmelCase		:			str							)      ->				str:
      SCREAMING_SNAKE_CASE_		,				SCREAMING_SNAKE_CASE_					=    get_position(__UpperCAmelCase    ,    char.upper()							)
      if row == 1:
            return table[0][col]
      else:
            return table[1][col] if row == 0 else char


if __name__ == "__main__":
   import doctest

   doctest.testmod()  # Fist ensure that all our tests are passing...
   lowerCamelCase__				:     Tuple			       =							input('Enter key: ').strip()
   lowerCamelCase__				:     Optional[Any]			       =							input('Enter text to encrypt: ').strip()
   lowerCamelCase__				:     Union[str, Any]			       =							encrypt(key, text)

   print(f'''Encrypted: {cipher_text}''')
   print(f'''Decrypted with key: {decrypt(key, cipher_text)}''')





import os
from pathlib import Path
from typing import Dict, List

import fire
import torch

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.utils.logging import get_logger


lowerCamelCase__				:     Optional[Any]			       =							get_logger(__name__)

def       UpperCAmelCase_							(   __UpperCAmelCase		:			str    ,    __UpperCAmelCase		:			str							)      ->				List[str]:
      if text.startswith(__UpperCAmelCase							):
            return text[len(__UpperCAmelCase							) :]
      return text  # or whatever

def       UpperCAmelCase_							(   __UpperCAmelCase		:			Union[str, Any]							)      ->				List[Any]:
      return {remove_prefix(__UpperCAmelCase    ,    'model.'							): v for k, v in sd.items()}

def       UpperCAmelCase_							(   __UpperCAmelCase		:			List[Dict[str, torch.Tensor]]							)      ->				Dict:
      SCREAMING_SNAKE_CASE_					=    {}
      for k in state_dicts[0].keys():
            SCREAMING_SNAKE_CASE_					=    [sd[k] for sd in state_dicts]
            SCREAMING_SNAKE_CASE_					=    sum(__UpperCAmelCase							) / len(__UpperCAmelCase							)
            assert isinstance(__UpperCAmelCase    ,    torch.Tensor							)
            SCREAMING_SNAKE_CASE_					=    new_t
      return new_sd

def       UpperCAmelCase_							(   __UpperCAmelCase		:			str    ,    __UpperCAmelCase		:			str    ,    __UpperCAmelCase		:			str							)      ->				None:
      SCREAMING_SNAKE_CASE_					=    AutoModelForSeqaSeqLM.from_pretrained(__UpperCAmelCase							)
      if os.path.isfile(__UpperCAmelCase							):
            SCREAMING_SNAKE_CASE_					=    [pl_ckpt_path]
      else:
            assert os.path.isdir(__UpperCAmelCase							)
            SCREAMING_SNAKE_CASE_					=    list(Path(__UpperCAmelCase							).glob('*.ckpt'							)							)
            assert ckpt_files, f"could not find any ckpt files inside the {pl_ckpt_path} directory"

      if len(__UpperCAmelCase							) > 1:
            logger.info(f"averaging the weights of {ckpt_files}"							)

      SCREAMING_SNAKE_CASE_					=    [sanitize(torch.load(__UpperCAmelCase    ,    map_location='cpu'							)['state_dict']							) for x in ckpt_files]
      SCREAMING_SNAKE_CASE_					=    average_state_dicts(__UpperCAmelCase							)

      SCREAMING_SNAKE_CASE_		,				SCREAMING_SNAKE_CASE_					=    hf_model.load_state_dict(__UpperCAmelCase    ,    strict=__UpperCAmelCase							)
      assert not missing, f"missing keys: {missing}"
      hf_model.save_pretrained(__UpperCAmelCase							)
      try:
            SCREAMING_SNAKE_CASE_					=    AutoTokenizer.from_pretrained(__UpperCAmelCase							)
            tok.save_pretrained(__UpperCAmelCase							)
      except Exception:
            pass
            # dont copy tokenizer if cant


if __name__ == "__main__":
   fire.Fire(convert_pl_to_hf)