
"""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    =		logging.get_logger(__name__)

snake_case    =		{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

snake_case    =		{
    '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    =		{
    'openai/clip-vit-base-patch32': 7_7,
}




class      UpperCamelCase	(       __magic_name__      ):

				"""simple docstring"""



				UpperCAmelCase_				:      List[Any]						  =				VOCAB_FILES_NAMES
				UpperCAmelCase_				:      Union[str, Any]						  =				PRETRAINED_VOCAB_FILES_MAP
				UpperCAmelCase_				:      str						  =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				UpperCAmelCase_				:      str						  =				["input_ids", "attention_mask"]
				UpperCAmelCase_				:      Optional[Any]						  =				CLIPTokenizer


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







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

									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			)    ->    Tuple:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	self.backend_tokenizer.decode

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

									SCREAMING_SNAKE_CASE				=	new_decode_method


				def 							A					(				self		,	lowercase__		,	lowercase__ = None			)    ->    List[int]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	[self.bos_token_id]
									SCREAMING_SNAKE_CASE				=	[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		,	lowercase__		,	lowercase__ = None			)    ->    List[int]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	[self.bos_token_id]
									SCREAMING_SNAKE_CASE				=	[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		,	lowercase__		,	lowercase__ = None			)    ->    Tuple[str]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	self._tokenizer.model.save(lowercase__		,	name=lowercase__			)
									return tuple(lowercase__			)


"""simple docstring"""




from functools import lru_cache

@lru_cache
def   UpperCamelCase_  (		SCREAMING_SNAKE_CASE_			):
					if not isinstance(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_			):
										raise TypeError('k must be an integer.'			)
					if k < 0:
										raise ValueError('k integer must be greater or equal to zero.'			)
					if k == 0:
										return 0
					elif k == 1:
										return 1
					else:
										return fibonacci(k - 1			) + fibonacci(k - 2			)

def   UpperCamelCase_  (		SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_			):
					SCREAMING_SNAKE_CASE				=	len(SCREAMING_SNAKE_CASE_			)
					# Find m such that F_m >= n where F_i is the i_th fibonacci number.
					SCREAMING_SNAKE_CASE				=	0
					while True:
										if fibonacci(SCREAMING_SNAKE_CASE_			) >= len_list:
															SCREAMING_SNAKE_CASE				=	i
															break
										i += 1
					SCREAMING_SNAKE_CASE				=	0
					while fibb_k > 0:
										SCREAMING_SNAKE_CASE				=	min(
										    offset + fibonacci(fibb_k - 1			),     len_list - 1			)  # Prevent out of range
										SCREAMING_SNAKE_CASE				=	arr[index_k]
										if item_k_1 == val:
															return index_k
										elif val < item_k_1:
															fibb_k -= 1
										elif val > item_k_1:
															offset += fibonacci(fibb_k - 1			)
															fibb_k -= 2
					else:
										return -1


if __name__ == "__main__":
	import doctest

	doctest.testmod()
