





'''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


_lowerCamelCase					:						List[Any]					     =							logging.get_logger(__name__)

_lowerCamelCase					:						Union[str, Any]					     =							{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

_lowerCamelCase					:						int					     =							{
    """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"""
        ),
    },
}

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



class 				__UpperCAmelCase	(							_SCREAMING_SNAKE_CASE    ):







		'''simple docstring'''







		__lowerCAmelCase								=     VOCAB_FILES_NAMES
		__lowerCAmelCase								=     PRETRAINED_VOCAB_FILES_MAP
		__lowerCAmelCase								=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		__lowerCAmelCase								=     ['''input_ids''', '''attention_mask''']
		__lowerCAmelCase								=     CLIPTokenizer







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

			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 							A  (self    :   Any   ):
			A					=   self.backend_tokenizer.decode

			def new_decode_method(*_lowerCAmelCase    :   Dict   ,   **_lowerCAmelCase    :   str   ):
				A					=   orig_decode_method(*__A   ,   **__A   )
				A					=   text.replace(self.backend_tokenizer.model.end_of_word_suffix   ,   """ """   ).strip()
				return text

			A					=   new_decode_method







		def 							A  (self    :   Any   ,   _lowerCAmelCase    :   Optional[int]   ,   _lowerCAmelCase    :   Optional[int] = None   ):
			A					=   [self.bos_token_id]
			A					=   [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 							A  (self    :   List[Any]   ,   _lowerCAmelCase    :   List[str]   ,   _lowerCAmelCase    :   List[str] = None   ):
			A					=   [self.bos_token_id]
			A					=   [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 							A  (self    :   List[Any]   ,   _lowerCAmelCase    :   Any   ,   _lowerCAmelCase    :   Union[str, Any] = None   ):
			A					=   self._tokenizer.model.save(__A   ,   name=__A   )
			return tuple(__A   )





"""simple docstring"""







from .stack import Stack
def _A		(		lowercase						):







    """simple docstring"""
    a											=Stack()
    a											={'''(''': ''')''', '''[''': ''']''', '''{''': '''}'''}
    for bracket in parentheses:
        if bracket in bracket_pairs:
            stack.push(lowercase						)
        elif bracket in (")", "]", "}"):
            if stack.is_empty() or bracket_pairs[stack.pop()] != bracket:
                return False
    return stack.is_empty()


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

       testmod()

       lowerCamelCase_  :  List[str]     		=    ["""((()))""", """((())""", """(()))"""]
       print("""Balanced parentheses demonstration:\n""")
       for example in examples:
              lowerCamelCase_  :  str     		=    """""" if balanced_parentheses(example) else """not """
              print(F'{example} is {not_str}balanced')