'''simple docstring'''
import os
import unittest

from transformers.models.bertweet.tokenization_bertweet import VOCAB_FILES_NAMES, BertweetTokenizer

from ...test_tokenization_common import TokenizerTesterMixin






class       __lowercase		(    A_      ,				unittest.TestCase    ):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		 =    BertweetTokenizer
     SCREAMING_SNAKE_CASE__		 =    False







     def lowerCAmelCase  (		self     ):
         super().setUp()

         # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
         __UpperCamelCase						:						str		     =	['I', 'm', 'V@@', 'R@@', 'r', 'e@@']
         __UpperCamelCase						:						Dict		     =	dict(zip(_A  ,      range(len(_A     )     )     )     )
         __UpperCamelCase						:						List[str]		     =	['#version: 0.2', 'a m</w>']
         __UpperCamelCase						:						Tuple		     =	{'unk_token': '<unk>'}

         __UpperCamelCase						:						str		     =	os.path.join(self.tmpdirname  ,      VOCAB_FILES_NAMES['vocab_file']     )
         __UpperCamelCase						:						str		     =	os.path.join(self.tmpdirname  ,      VOCAB_FILES_NAMES['merges_file']     )
         with open(self.vocab_file  ,      'w'  ,      encoding='utf-8'     ) as fp:
             for token in vocab_tokens:
                 fp.write(f"""{token} {vocab_tokens[token]}\n"""     )
         with open(self.merges_file  ,      'w'  ,      encoding='utf-8'     ) as fp:
             fp.write('\n'.join(_A     )     )







     def lowerCAmelCase  (		self  ,      **_lowerCamelCase     ):
         kwargs.update(self.special_tokens_map     )
         return BertweetTokenizer.from_pretrained(self.tmpdirname  ,      **_A     )







     def lowerCAmelCase  (		self  ,      _lowerCamelCase     ):
         __UpperCamelCase						:						Tuple		     =	'I am VinAI Research'
         __UpperCamelCase						:						int		     =	'I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'
         return input_text, output_text







     def lowerCAmelCase  (		self     ):
         __UpperCamelCase						:						Union[str, Any]		     =	BertweetTokenizer(self.vocab_file  ,      self.merges_file  ,      **self.special_tokens_map     )
         __UpperCamelCase						:						Dict		     =	'I am VinAI Research'
         __UpperCamelCase						:						int		     =	'I a@@ m V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'.split()
         __UpperCamelCase						:						Optional[Any]		     =	tokenizer.tokenize(_A     )
         self.assertListEqual(_A  ,      _A     )

         __UpperCamelCase						:						Tuple		     =	tokens + [tokenizer.unk_token]

         __UpperCamelCase						:						List[Any]		     =	[4, 3, 5, 6, 3, 3, 3, 4, 7, 9, 3, 9, 3, 3, 3, 3, 3]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(_A     )  ,      _A     )





_A       =					{
    "0": 1,
    "1": 1,
    "2": 2,
    "3": 6,
    "4": 24,
    "5": 1_20,
    "6": 7_20,
    "7": 50_40,
    "8": 4_03_20,
    "9": 36_28_80,
}

_A       =					{1_45: 1_45}

_A       =					{
    1_45: 0,
    1_69: 3,
    3_63_01: 3,
    14_54: 3,
    8_71: 2,
    4_53_61: 2,
    8_72: 2,
}



def 		lowercase_     (  A__						)				->				int:
    """simple docstring"""

    if n in CACHE_SUM_DIGIT_FACTORIALS:
        return CACHE_SUM_DIGIT_FACTORIALS[n]
    snake_case						=   sum(DIGIT_FACTORIALS[let] for let in str(A__						)						)
    snake_case						=   ret
    return ret



def 		lowercase_     (  A__					,						A__ = None						)				->				int:
    """simple docstring"""

    snake_case						=   previous or set()
    if n in CHAIN_LENGTH_CACHE:
        return CHAIN_LENGTH_CACHE[n]
    snake_case						=   sum_digit_factorials(A__						)
    if next_number in previous:
        snake_case						=   0
        return 0
    else:
        previous.add(A__						)
        snake_case						=   1 + chain_length(A__					,						A__						)
        snake_case						=   ret
        return ret



def 		lowercase_     (  A__ = 60					,						A__ = 100_0000						)				->				int:
    """simple docstring"""

    return sum(1 for i in range(1					,						A__						) if chain_length(A__						) == num_terms						)


if __name__ == "__main__":
   print(f"{solution() = }")

