
import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin



class       _snake_case   (	UpperCAmelCase_  ,						unittest.TestCase							):
 __lowerCAmelCase  :     Tuple        =			XLMTokenizer
 __lowerCAmelCase  :     Dict        =			False


 def      lowercase__     (					self):


   '''simple docstring'''




   super().setUp()

   # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
   lowercase__  :   Optional[int]    		=      [
       """l""",
       """o""",
       """w""",
       """e""",
       """r""",
       """s""",
       """t""",
       """i""",
       """d""",
       """n""",
       """w</w>""",
       """r</w>""",
       """t</w>""",
       """lo""",
       """low""",
       """er</w>""",
       """low</w>""",
       """lowest</w>""",
       """newer</w>""",
       """wider</w>""",
       """<unk>""",
   ]
   lowercase__  :   Any    		=      dict(zip(SCREAMING_SNAKE_CASE_					,  range(len(SCREAMING_SNAKE_CASE_))))
   lowercase__  :   int    		=      ["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

   lowercase__  :   int    		=      os.path.join(self.tmpdirname					,  VOCAB_FILES_NAMES["""vocab_file"""])
   lowercase__  :   Optional[int]    		=      os.path.join(self.tmpdirname					,  VOCAB_FILES_NAMES["""merges_file"""])
   with open(self.vocab_file					,  """w""") as fp:
     fp.write(json.dumps(SCREAMING_SNAKE_CASE_))
   with open(self.merges_file					,  """w""") as fp:
     fp.write("""\n""".join(SCREAMING_SNAKE_CASE_))


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   Tuple    		=      """lower newer"""
   lowercase__  :   List[str]    		=      """lower newer"""
   return input_text, output_text


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   Union[str, Any]    		=      XLMTokenizer(self.vocab_file					,  self.merges_file)

   lowercase__  :   Any    		=      """lower"""
   lowercase__  :   str    		=      ["""low""", """er</w>"""]
   lowercase__  :   str    		=      tokenizer.tokenize(SCREAMING_SNAKE_CASE_)
   self.assertListEqual(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)

   lowercase__  :   Any    		=      tokens + ["""<unk>"""]
   lowercase__  :   List[Any]    		=      [14, 15, 20]
   self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_)					,  SCREAMING_SNAKE_CASE_)



 @slow
 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   Tuple    		=      XLMTokenizer.from_pretrained("""xlm-mlm-en-2048""")

   lowercase__  :   str    		=      tokenizer.encode("""sequence builders"""					,  add_special_tokens=SCREAMING_SNAKE_CASE_)
   lowercase__  :   Any    		=      tokenizer.encode("""multi-sequence build"""					,  add_special_tokens=SCREAMING_SNAKE_CASE_)

   lowercase__  :   Dict    		=      tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE_)
   lowercase__  :   Any    		=      tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)

   assert encoded_sentence == [0] + text + [1]
   assert encoded_pair == [0] + text + [1] + text_a + [1]








from math import factorial

lowerCamelCase__    :		dict[str, int]          =   {str(digit): factorial(digit) for digit in range(1_0)}

def 		UpperCamelCase	(      lowercase_   )		->	int:


  '''simple docstring'''






  if not isinstance(lowercase_ , lowercase_   ):
    raise TypeError("""Parameter number must be int"""   )

  if number < 0:
    raise ValueError("""Parameter number must be greater than or equal to 0"""   )

  # Converts number in string to iterate on its digits and adds its factorial.
  return sum(DIGIT_FACTORIAL[digit] for digit in str(lowercase_   )   )

def 		UpperCamelCase	(      lowercase_ = 60 , lowercase_ = 1_00_00_00   )		->	int:


  '''simple docstring'''






  if not isinstance(lowercase_ , lowercase_   ) or not isinstance(lowercase_ , lowercase_   ):
    raise TypeError("""Parameters chain_length and number_limit must be int"""   )

  if chain_length <= 0 or number_limit <= 0:
    raise ValueError(
        """Parameters chain_length and number_limit must be greater than 0"""   )

  # the counter for the chains with the exact desired length
  lowercase__  :   List[Any]    		=      0
  # the cached sizes of the previous chains
  lowercase__  :   dict[int, int]    		=      {}

  for start_chain_element in range(1 , lowercase_   ):
    # The temporary set will contain the elements of the chain
    lowercase__  :   Optional[Any]    		=      set()
    lowercase__  :   Union[str, Any]    		=      0

    # Stop computing the chain when you find a cached size, a repeating item or the
    # length is greater then the desired one.
    lowercase__  :   Union[str, Any]    		=      start_chain_element
    while (
        chain_element not in chain_sets_lengths
        and chain_element not in chain_set
        and chain_set_length <= chain_length
    ):
      chain_set.add(lowercase_   )
      chain_set_length += 1
      lowercase__  :   str    		=      digit_factorial_sum(lowercase_   )

    if chain_element in chain_sets_lengths:
      chain_set_length += chain_sets_lengths[chain_element]

    lowercase__  :   str    		=      chain_set_length

    # If chain contains the exact amount of elements increase the counter
    if chain_set_length == chain_length:
      chains_counter += 1

  return chains_counter


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     print(f'''{solution()}''')






