


'''simple docstring'''

from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_clip import CLIPTokenizer


__snake_case       :   str  		=    logging.get_logger(__name__)

__snake_case       :   str  		=    {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

__snake_case       :   Union[str, Any]  		=    {
    """vocab_file""": {
        """openai/clip-vit-base-patch32""": """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """openai/clip-vit-base-patch32""": """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/merges.txt""",
    },
    """tokenizer_file""": {
        """openai/clip-vit-base-patch32""": (
            """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/tokenizer.json"""
        ),
    },
}

__snake_case       :   Optional[int]  		=    {
    """openai/clip-vit-base-patch32""": 77,
}
class 							lowercase_    (     __lowerCamelCase						):
    a_             =   VOCAB_FILES_NAMES
    a_             =   PRETRAINED_VOCAB_FILES_MAP
    a_             =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a_             =   ["""input_ids""", """attention_mask"""]
    a_             =   CLIPTokenizer







    def __init__(	self       ,     UpperCamelCase__=None       ,     UpperCamelCase__=None       ,     UpperCamelCase__=None       ,     UpperCamelCase__="<|endoftext|>"       ,     UpperCamelCase__="<|startoftext|>"       ,     UpperCamelCase__="<|endoftext|>"       ,     UpperCamelCase__="<|endoftext|>"       ,     **UpperCamelCase__       ,     )				->       Union[str, Any]:





     """simple docstring"""

     super().__init__(
         _lowerCAmelCase       ,     _lowerCAmelCase       ,     tokenizer_file=_lowerCAmelCase       ,     unk_token=_lowerCAmelCase       ,     bos_token=_lowerCAmelCase       ,     eos_token=_lowerCAmelCase       ,     pad_token=_lowerCAmelCase       ,     **_lowerCAmelCase       ,     )

     if not isinstance(self.backend_tokenizer.pre_tokenizer       ,     pre_tokenizers.Sequence				):
      raise ValueError(
          "The `backend_tokenizer` provided does not match the expected format. The CLIP tokenizer has been"
          " heavily modified from transformers version 4.17.0. You need to convert the tokenizer you are using"
          " to be compatible with this version.The easiest way to do so is"
          " `CLIPTokenizerFast.from_pretrained(\"path_to_local_folder_or_hub_repo, from_slow=True)`. If you want"
          " to use your existing tokenizer, you will have to revert to a version prior to 4.17.0 of"
          " transformers."				)

     self._wrap_decode_method_backend_tokenizer()







    def   lowerCamelCase_    (	self				)				->       Optional[Any]:





     """simple docstring"""

     UpperCAmelCase_				       =					self.backend_tokenizer.decode

     def new_decode_method(*UpperCamelCase__       ,     **UpperCamelCase__				):
      UpperCAmelCase_				       =					orig_decode_method(*_lowerCAmelCase       ,     **_lowerCAmelCase				)
      UpperCAmelCase_				       =					text.replace(self.backend_tokenizer.model.end_of_word_suffix       ,     " "				).strip()
      return text

     UpperCAmelCase_				       =					new_decode_method







    def   lowerCamelCase_    (	self       ,     UpperCamelCase__       ,     UpperCamelCase__ = None				)				->       Union[str, Any]:





     """simple docstring"""

     UpperCAmelCase_				       =					[self.bos_token_id]
     UpperCAmelCase_				       =					[self.eos_token_id]

     if token_ids_a is None:
      return bos_token + token_ids_a + eos_token
     return bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token







    def   lowerCamelCase_    (	self       ,     UpperCamelCase__       ,     UpperCamelCase__ = None				)				->       Optional[Any]:





     """simple docstring"""

     UpperCAmelCase_				       =					[self.bos_token_id]
     UpperCAmelCase_				       =					[self.eos_token_id]

     if token_ids_a is None:
      return len(bos_token + token_ids_a + eos_token				) * [0]
     return len(bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token				) * [0]







    def   lowerCamelCase_    (	self       ,     UpperCamelCase__       ,     UpperCamelCase__ = None				)				->       int:





     """simple docstring"""

     UpperCAmelCase_				       =					self._tokenizer.model.save(_lowerCAmelCase       ,     name=_lowerCAmelCase				)
     return tuple(_lowerCAmelCase				)

'''simple docstring'''

def lowerCamelCase__						(       A_       ):
 UpperCAmelCase_				       =					len(A_       )
 for _ in range(
     0       ,			int(((no_of_elements - 1) / 2) + 1       )       ):  # we don't need to traverse to end of list as
  for j in range(0       ,			no_of_elements - 1       ):
   if (
       lst[j + 1] < lst[j]
   ):  # applying bubble sort algorithm from left to right (or forwards)
    UpperCAmelCase_				       =					lst[j + 1]
    UpperCAmelCase_				       =					lst[j]
    UpperCAmelCase_				       =					temp
   if (
       lst[no_of_elements - 1 - j] < lst[no_of_elements - 2 - j]
   ):  # applying bubble sort algorithm from right to left (or backwards)
    UpperCAmelCase_				       =					lst[no_of_elements - 1 - j]
    UpperCAmelCase_				       =					lst[no_of_elements - 2 - j]
    UpperCAmelCase_				       =					temp
 return lst


if __name__ == "__main__":
      print('''enter the list to be sorted''')
      __snake_case       :   List[str]  		=    [int(x) for x in input().split()]  # inputing elements of the list in one line
      __snake_case       :   Optional[int]  		=    double_sort(lst)
      print('''the sorted list is''')
      print(sorted_lst)
