





def     lowerCamelCase_	(      lowerCAmelCase:	int				)->		list:
  _snake_case   :				List[Any]														=	int(lowerCAmelCase				)
  if n_element < 1:
    _snake_case   :				int														=	ValueError('a should be a positive number'				)
    raise my_error

  _snake_case   :				Union[str, Any]														=	[1]
  _snake_case							,					_snake_case							,					_snake_case   :				Any														=	(0, 0, 0)
  _snake_case   :				str														=	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__":
      lowerCAmelCase_						   =    input("""Enter the last number (nth term) of the Hamming Number Series: """)
      print("""Formula of Hamming Number Series => 2^i * 3^j * 5^k""")
      lowerCAmelCase_						   =    hamming(int(n))
      print("""-----------------------------------------------------""")
      print(F"""The list with nth numbers is: {hamming_numbers}""")
      print("""-----------------------------------------------------""")











import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer


lowerCAmelCase_						   =    {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

lowerCAmelCase_						   =    {
    """vocab_file""": {
        """unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/vocab.txt""",
    },
    """tokenizer_file""": {
        """unc-nlp/lxmert-base-uncased""": (
            """https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/tokenizer.json"""
        ),
    },
}

lowerCAmelCase_						   =    {
    """unc-nlp/lxmert-base-uncased""": 512,
}

lowerCAmelCase_						   =    {
    """unc-nlp/lxmert-base-uncased""": {"""do_lower_case""": True},
}



class        _lowerCAmelCase    (			UpperCAmelCase_							):


  '''simple docstring'''
  a_							:       List[Any]      					=VOCAB_FILES_NAMES
  a_							:       Tuple      					=PRETRAINED_VOCAB_FILES_MAP
  a_							:       Optional[Any]      					=PRETRAINED_INIT_CONFIGURATION
  a_							:       Any      					=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  a_							:       Any      					=LxmertTokenizer







  def __init__(      self      :					Any      ,				UpperCamelCase      :					Union[str, Any]=None      ,				UpperCamelCase      :					Dict=None      ,				UpperCamelCase      :					List[str]=True      ,				UpperCamelCase      :					List[str]="[UNK]"      ,				UpperCamelCase      :					List[Any]="[SEP]"      ,				UpperCamelCase      :					List[Any]="[PAD]"      ,				UpperCamelCase      :					Optional[Any]="[CLS]"      ,				UpperCamelCase      :					Optional[int]="[MASK]"      ,				UpperCamelCase      :					Optional[int]=True      ,				UpperCamelCase      :					str=None      ,				**UpperCamelCase      :					List[str]      ,				):


    '''simple docstring'''





    super().__init__(
        UpperCamelCase      ,				tokenizer_file=UpperCamelCase      ,				do_lower_case=UpperCamelCase      ,				unk_token=UpperCamelCase      ,				sep_token=UpperCamelCase      ,				pad_token=UpperCamelCase      ,				cls_token=UpperCamelCase      ,				mask_token=UpperCamelCase      ,				tokenize_chinese_chars=UpperCamelCase      ,				strip_accents=UpperCamelCase      ,				**UpperCamelCase      ,				)

    _snake_case   :				Tuple														=	json.loads(self.backend_tokenizer.normalizer.__getstate__()							)
    if (
        normalizer_state.get('lowercase'      ,				UpperCamelCase							) != do_lower_case
        or normalizer_state.get('strip_accents'      ,				UpperCamelCase							) != strip_accents
        or normalizer_state.get('handle_chinese_chars'      ,				UpperCamelCase							) != tokenize_chinese_chars
    ):
      _snake_case   :				List[Any]														=	getattr(UpperCamelCase      ,				normalizer_state.pop('type'							)							)
      _snake_case   :				Optional[int]														=	do_lower_case
      _snake_case   :				Dict														=	strip_accents
      _snake_case   :				Optional[int]														=	tokenize_chinese_chars
      _snake_case   :				Optional[Any]														=	normalizer_class(**UpperCamelCase							)

    _snake_case   :				int														=	do_lower_case







  def UpperCamelCase_ (      self      :					int      ,				UpperCamelCase      :					List[str]      ,				UpperCamelCase      :					str=None							):


    '''simple docstring'''





    _snake_case   :				List[Any]														=	[self.cls_token_id] + token_ids_a + [self.sep_token_id]

    if token_ids_a:
      output += token_ids_a + [self.sep_token_id]

    return output







  def UpperCamelCase_ (      self      :					List[str]      ,				UpperCamelCase      :					List[int]      ,				UpperCamelCase      :					Optional[List[int]] = None							):


    '''simple docstring'''





    _snake_case   :				Tuple														=	[self.sep_token_id]
    _snake_case   :				List[str]														=	[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							) * [0] + len(token_ids_a + sep							) * [1]







  def UpperCamelCase_ (      self      :					int      ,				UpperCamelCase      :					str      ,				UpperCamelCase      :					Optional[str] = None							):


    '''simple docstring'''





    _snake_case   :				int														=	self._tokenizer.model.save(UpperCamelCase      ,				name=UpperCamelCase							)
    return tuple(UpperCamelCase							)




