




'''simple docstring'''




import functools
from math import sqrt
from time import time





def   a_							(   __snake_case							:    Optional[Any]     , *__snake_case							:    Optional[Any]     , **__snake_case							:    Any     )							->		Optional[Any]:



       """simple docstring"""
       lowerCamelCase_							=time()
       lowerCamelCase_							=func(*__A     , **__A     )
       lowerCamelCase_							=time()
       if int(end - start     ) > 0:
              print(F'''{func.__name__} runtime: {(end - start):0.4f} s'''     )
       else:
              print(F'''{func.__name__} runtime: {(end - start) * 1000:0.4f} ms'''     )
       return output





def   a_							(   __snake_case							:    Union[str, Any]     )							->		str:



       """simple docstring"""



       if n < 0:
              raise Exception('''n is negative'''     )
       if n == 0:
              return [0]
       lowerCamelCase_							=[0, 1]
       for _ in range(n - 1     ):
              fib.append(fib[-1] + fib[-2]     )
       return fib





def   a_							(   __snake_case							:    Union[str, Any]     )							->		List[str]:



       """simple docstring"""



       def fib_recursive_term(__snake_case							:    List[str]     ) -> int:
              if i < 0:
                     raise Exception('''n is negative'''     )
              if i < 2:
                     return i
              return fib_recursive_term(i - 1     ) + fib_recursive_term(i - 2     )

       if n < 0:
              raise Exception('''n is negative'''     )
       return [fib_recursive_term(__A     ) for i in range(n + 1     )]





def   a_							(   __snake_case							:    Dict     )							->		Union[str, Any]:



       """simple docstring"""



       @functools.cache
       def fib_recursive_term(__snake_case							:    List[Any]     ) -> int:
              if i < 0:
                     raise Exception('''n is negative'''     )
              if i < 2:
                     return i
              return fib_recursive_term(i - 1     ) + fib_recursive_term(i - 2     )

       if n < 0:
              raise Exception('''n is negative'''     )
       return [fib_recursive_term(__A     ) for i in range(n + 1     )]





def   a_							(   __snake_case							:    Tuple     )							->		str:



       """simple docstring"""



       if n < 0:
              raise Exception('''n is negative'''     )
       # Cache must be outside recursuive function
       # other it will reset every time it calls itself.
       lowerCamelCase_							={0: 0, 1: 1, 2: 1}  # Prefilled cache

       def rec_fn_memoized(__snake_case							:    Optional[int]     ) -> int:
              if num in cache:
                     return cache[num]

              lowerCamelCase_							=rec_fn_memoized(num - 1     ) + rec_fn_memoized(num - 2     )
              lowerCamelCase_							=value
              return value

       return [rec_fn_memoized(__A     ) for i in range(n + 1     )]





def   a_							(   __snake_case							:    Dict     )							->		Tuple:



       """simple docstring"""



       if n < 0:
              raise Exception('''n is negative'''     )
       if n >= 1475:
              raise Exception('''n is too large'''     )
       lowerCamelCase_							=sqrt(5     )
       lowerCamelCase_							=(1 + sqrt_a) / 2
       return [round(phi**i / sqrt_a     ) for i in range(n + 1     )]


if __name__ == "__main__":
     a_   :	Optional[Any]							   = 30
     time_func(fib_iterative, num)
     time_func(fib_recursive, num)  # Around 3s runtime
     time_func(fib_recursive_cached, num)  # Around 0ms runtime
     time_func(fib_memoization, num)
     time_func(fib_binet, num)







'''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


a_   :	Tuple							   = logging.get_logger(__name__)

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

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


class 						__UpperCamelCase (				lowerCamelCase__       ):
       lowercase			:					Union[str, Any]   		=VOCAB_FILES_NAMES
       lowercase			:					Optional[int]   		=PRETRAINED_VOCAB_FILES_MAP
       lowercase			:					Any   		=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowercase			:					str   		=['input_ids', 'attention_mask']
       lowercase			:					List[Any]   		=CLIPTokenizer






       def __init__(							self,	lowerCAmelCase=None,	lowerCAmelCase=None,	lowerCAmelCase=None,	lowerCAmelCase="<|endoftext|>",	lowerCAmelCase="<|startoftext|>",	lowerCAmelCase="<|endoftext|>",	lowerCAmelCase="<|endoftext|>",	**lowerCAmelCase,	):



              """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   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.backend_tokenizer.decode

              def new_decode_method(*lowerCAmelCase,	**lowerCAmelCase						):
                     lowerCamelCase_							=orig_decode_method(*lowerCAmelCase,	**lowerCAmelCase						)
                     lowerCamelCase_							=text.replace(self.backend_tokenizer.model.end_of_word_suffix,	''' '''						).strip()
                     return text

              lowerCamelCase_							=new_decode_method






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase = None						):



              """simple docstring"""







              lowerCamelCase_							=[self.bos_token_id]
              lowerCamelCase_							=[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   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase = None						):



              """simple docstring"""







              lowerCamelCase_							=[self.bos_token_id]
              lowerCamelCase_							=[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   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase = None						):



              """simple docstring"""







              lowerCamelCase_							=self._tokenizer.model.save(lowerCAmelCase,	name=lowerCAmelCase						)
              return tuple(lowerCAmelCase						)




