




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


a_										=       logging.get_logger(__name__)

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

a_										=       {
    "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"
        ),
    },
}

a_										=       {
    "openai/clip-vit-base-patch32": 77,
}

class 	_lowerCamelCase  (     _SCREAMING_SNAKE_CASE				):

      """simple docstring"""

      lowerCAmelCase__     :	Any      =   VOCAB_FILES_NAMES
      lowerCAmelCase__     :	Union[str, Any]      =   PRETRAINED_VOCAB_FILES_MAP
      lowerCAmelCase__     :	Any      =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      lowerCAmelCase__     :	Union[str, Any]      =   ["input_ids", "attention_mask"]
      lowerCAmelCase__     :	Union[str, Any]      =   CLIPTokenizer







      def __init__(       self   :	Union[str, Any]	,    snake_case   :	Tuple=None	,    snake_case   :	Optional[Any]=None	,    snake_case   :	Optional[Any]=None	,    snake_case   :	str="<|endoftext|>"	,    snake_case   :	int="<|startoftext|>"	,    snake_case   :	Dict="<|endoftext|>"	,    snake_case   :	List[str]="<|endoftext|>"	,    **snake_case   :	Tuple	,    ):
          super().__init__(
              snake_case	,    snake_case	,    tokenizer_file=snake_case	,    unk_token=snake_case	,    bos_token=snake_case	,    eos_token=snake_case	,    pad_token=snake_case	,    **snake_case	,    )

          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  snake_case		(       self   :	Optional[int]			):
          __UpperCamelCase											=  self.backend_tokenizer.decode

          def new_decode_method(*snake_case   :	int	,    **snake_case   :	List[str]			):
              __UpperCamelCase											=  orig_decode_method(*snake_case	,    **snake_case			)
              __UpperCamelCase											=  text.replace(self.backend_tokenizer.model.end_of_word_suffix	,    ''' '''			).strip()
              return text

          __UpperCamelCase											=  new_decode_method







      def  snake_case		(       self   :	List[str]	,    snake_case   :	List[int]	,    snake_case   :	Optional[List[int]] = None			):
          __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  snake_case		(       self   :	Union[str, Any]	,    snake_case   :	List[int]	,    snake_case   :	Optional[List[int]] = None			):
          __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  snake_case		(       self   :	List[Any]	,    snake_case   :	str	,    snake_case   :	Optional[str] = None			):
          __UpperCamelCase											=  self._tokenizer.model.save(snake_case	,    name=snake_case			)
          return tuple(snake_case			)












def    __SCREAMING_SNAKE_CASE				(					lowercase_ )    ->		int:

    """simple docstring"""


    if not isinstance(lowercase_   ,       lowercase_ ):
        raise TypeError('''recursive_lucas_number accepts only integer arguments.''' )
    if n_th_number == 0:
        return 2
    if n_th_number == 1:
        return 1

    return recursive_lucas_number(n_th_number - 1 ) + recursive_lucas_number(
        n_th_number - 2 )




def    __SCREAMING_SNAKE_CASE				(					lowercase_ )    ->		int:

    """simple docstring"""


    if not isinstance(lowercase_   ,       lowercase_ ):
        raise TypeError('''dynamic_lucas_number accepts only integer arguments.''' )
    __UpperCamelCase						, __UpperCamelCase											=  2, 1
    for _ in range(lowercase_ ):
        __UpperCamelCase						, __UpperCamelCase											=  b, a + b
    return a


if __name__ == "__main__":
 from doctest import testmod

 testmod()
 a_										=       int(input("Enter the number of terms in lucas series:\n").strip())
 print("Using recursive function to calculate lucas series:")
 print(" ".join(str(recursive_lucas_number(i)) for i in range(n)))
 print("\nUsing dynamic function to calculate lucas series:")
 print(" ".join(str(dynamic_lucas_number(i)) for i in range(n)))






