






import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
   from .tokenization_camembert import CamembertTokenizer
else:
   A_						:						int						      =					None


A_						:						str						      =					logging.get_logger(__name__)

A_						:						List[Any]						      =					{'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

A_						:						Any						      =					{
    'vocab_file': {
        'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model',
    },
    'tokenizer_file': {
        'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/tokenizer.json',
    },
}

A_						:						Tuple						      =					{
    'camembert-base': 512,
}

A_						:						List[Any]						      =					'▁'




class 							_lowerCAmelCase(			UpperCAmelCase_   ):





       """simple docstring"""







       a							:						Dict										=VOCAB_FILES_NAMES
       a							:						Union[str, Any]										=PRETRAINED_VOCAB_FILES_MAP
       a							:						Optional[Any]										=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       a							:						Dict										=['''input_ids''', '''attention_mask''']
       a							:						List[Any]										=CamembertTokenizer





       def __init__(   self    ,     _lowerCamelCase=None    ,     _lowerCamelCase=None    ,     _lowerCamelCase="<s>"    ,     _lowerCamelCase="</s>"    ,     _lowerCamelCase="</s>"    ,     _lowerCamelCase="<s>"    ,     _lowerCamelCase="<unk>"    ,     _lowerCamelCase="<pad>"    ,     _lowerCamelCase="<mask>"    ,     _lowerCamelCase=["<s>NOTUSED", "</s>NOTUSED"]    ,     **_lowerCamelCase    ,     ):
         # Mask token behave like a normal word, i.e. include the space before it
         UpperCamelCase_:   Optional[int]        =							AddedToken(_lowerCamelCase    ,     lstrip=_lowerCamelCase    ,     rstrip=_lowerCamelCase				) if isinstance(_lowerCamelCase    ,     _lowerCamelCase				) else mask_token

         super().__init__(
             _lowerCamelCase    ,     tokenizer_file=_lowerCamelCase    ,     bos_token=_lowerCamelCase    ,     eos_token=_lowerCamelCase    ,     sep_token=_lowerCamelCase    ,     cls_token=_lowerCamelCase    ,     unk_token=_lowerCamelCase    ,     pad_token=_lowerCamelCase    ,     mask_token=_lowerCamelCase    ,     additional_special_tokens=_lowerCamelCase    ,     **_lowerCamelCase    ,     )

         UpperCamelCase_:   Union[str, Any]        =							vocab_file
         UpperCamelCase_:   Tuple        =							False if not self.vocab_file else True





       def      _a       (   self    ,     _lowerCamelCase    ,     _lowerCamelCase = None				):

         if token_ids_a is None:
           return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
         UpperCamelCase_:   List[Any]        =							[self.cls_token_id]
         UpperCamelCase_:   Tuple        =							[self.sep_token_id]
         return cls + token_ids_a + sep + sep + token_ids_a + sep





       def      _a       (   self    ,     _lowerCamelCase    ,     _lowerCamelCase = None				):
         UpperCamelCase_:   List[Any]        =							[self.sep_token_id]
         UpperCamelCase_:   Tuple        =							[self.cls_token_id]

         if token_ids_a is None:
           return len(cls + token_ids_a + sep				) * [0]
         return len(cls + token_ids_a + sep + sep + token_ids_a + sep				) * [0]





       def      _a       (   self    ,     _lowerCamelCase    ,     _lowerCamelCase = None				):
         if not self.can_save_slow_tokenizer:
           raise ValueError(
               'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
               'tokenizer.'				)

         if not os.path.isdir(_lowerCamelCase				):
           logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''				)
           return
         UpperCamelCase_:   int        =							os.path.join(
             _lowerCamelCase    ,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']				)

         if os.path.abspath(self.vocab_file				) != os.path.abspath(_lowerCamelCase				):
           copyfile(self.vocab_file    ,     _lowerCamelCase				)

         return (out_vocab_file,)





'''simple docstring'''


def 						lowerCamelCase__   (				a							):
						__snake_case						 =   int(a							)
						if n_element < 1:
												__snake_case						 =   ValueError('a should be a positive number'							)
												raise my_error

						__snake_case						 =   [1]
						__snake_case ,       __snake_case ,       __snake_case						 =   (0, 0, 0)
						__snake_case						 =   1
						while index < n_element:
												while hamming_list[i] * 2 <= hamming_list[-1]:
																		i += 1
												while hamming_list[j] * 3 <= hamming_list[-1]:
																		j += 1
												while hamming_list[k] * 5 <= hamming_list[-1]:
																		k += 1
												hamming_list.append(
												    min(hamming_list[i] * 2    ,	hamming_list[j] * 3    ,	hamming_list[k] * 5							)							)
												index += 1
						return hamming_list


if __name__ == "__main__":
	_lowercase  =			input("""Enter the last number (nth term) of the Hamming Number Series: """)
	print("""Formula of Hamming Number Series => 2^i * 3^j * 5^k""")
	_lowercase  =			hamming(int(n))
	print("""-----------------------------------------------------""")
	print(f'''The list with nth numbers is: {hamming_numbers}''')
	print("""-----------------------------------------------------""")

