





import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
A_		:		Union[str, Any]		     =			{
    '''E''': 12.70,
    '''T''': 9.06,
    '''A''': 8.17,
    '''O''': 7.51,
    '''I''': 6.97,
    '''N''': 6.75,
    '''S''': 6.33,
    '''H''': 6.09,
    '''R''': 5.99,
    '''D''': 4.25,
    '''L''': 4.03,
    '''C''': 2.78,
    '''U''': 2.76,
    '''M''': 2.41,
    '''W''': 2.36,
    '''F''': 2.23,
    '''G''': 2.02,
    '''Y''': 1.97,
    '''P''': 1.93,
    '''B''': 1.29,
    '''V''': 0.98,
    '''K''': 0.77,
    '''J''': 0.15,
    '''X''': 0.15,
    '''Q''': 0.10,
    '''Z''': 0.07,
}
A_		:		int		     =			'''ETAOINSHRDLCUMWFGYPBVKJXQZ'''
A_		:		str		     =			'''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''

def   snake_case (UpperCAmelCase__  )	->    dict[str, int]:
  UpperCamelCase_: Tuple   				=    {letter: 0 for letter in string.ascii_uppercase}
  for letter in message.upper():
    if letter in LETTERS:
      letter_count[letter] += 1

  return letter_count

def   snake_case (UpperCAmelCase__  )	->    str:
  return x[0]

def   snake_case (UpperCAmelCase__  )	->    str:
  UpperCamelCase_: Optional[int]   				=    get_letter_count(lowercase_  )
  UpperCamelCase_: List[str]   				=    {
      freq: [] for letter, freq in letter_to_freq.items()
  }
  for letter in LETTERS:
    freq_to_letter[letter_to_freq[letter]].append(lowercase_  )

  UpperCamelCase_: Optional[int]   				=    {}

  for freq in freq_to_letter:
    freq_to_letter[freq].sort(key=ETAOIN.find     ,   reverse=lowercase_  )
    UpperCamelCase_: Any   				=    ''.join(freq_to_letter[freq]  )

  UpperCamelCase_: Optional[int]   				=    list(freq_to_letter_str.items()  )
  freq_pairs.sort(key=lowercase_     ,   reverse=lowercase_  )

  UpperCamelCase_: str   				=    [freq_pair[1] for freq_pair in freq_pairs]

  return "".join(lowercase_  )

def   snake_case (UpperCAmelCase__  )	->    int:
  UpperCamelCase_: int   				=    get_frequency_order(lowercase_  )
  UpperCamelCase_: Any   				=    0
  for common_letter in ETAOIN[:6]:
    if common_letter in freq_order[:6]:
      match_score += 1

  for uncommon_letter in ETAOIN[-6:]:
    if uncommon_letter in freq_order[-6:]:
      match_score += 1

  return match_score


if __name__ == "__main__":
   import doctest

   doctest.testmod()







import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
   from transformers import AutoModelForSeqaSeqLM, AutoTokenizer




@require_torch
@require_sentencepiece
@require_tokenizers
class     _lowerCAmelCase(	unittest.TestCase ):





       """simple docstring"""







       @slow
       def       _a   ( self							):
         UpperCamelCase_: Optional[int]   				=    AutoModelForSeqaSeqLM.from_pretrained('google/mt5-small'  ,      return_dict=_lowerCamelCase							).to(_lowerCamelCase							)
         UpperCamelCase_: Dict   				=    AutoTokenizer.from_pretrained('google/mt5-small'							)

         UpperCamelCase_: Dict   				=    tokenizer('Hello there'  ,      return_tensors='pt'							).input_ids
         UpperCamelCase_: Optional[Any]   				=    tokenizer('Hi I am'  ,      return_tensors='pt'							).input_ids

         UpperCamelCase_: int   				=    model(input_ids.to(_lowerCamelCase							)  ,      labels=labels.to(_lowerCamelCase							)							).loss
         UpperCamelCase_: Tuple   				=    -(labels.shape[-1] * loss.item())

         UpperCamelCase_: Any   				=    -8_4.9_1_2_7
         self.assertTrue(abs(mtf_score - EXPECTED_SCORE							) < 1e-4							)