



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


__UpperCAmelCase    	=  logging.get_logger(__name__)

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

__UpperCAmelCase    	=  {
    '''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'''
        ),
    },
}

__UpperCAmelCase    	=  {
    '''openai/clip-vit-base-patch32''': 77,
}


class 						lowerCamelCase__			(		_a ):
						_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]   ,							_a    :	Tuple=None   ,							_a    :	Optional[int]=None   ,							_a    :	List[Any]=None   ,							_a    :	Dict="<|endoftext|>"   ,							_a    :	List[Any]="<|startoftext|>"   ,							_a    :	Any="<|endoftext|>"   ,							_a    :	Optional[int]="<|endoftext|>"   ,							**_a    :	str   ,							):
													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 	_lowerCamelCase      (			self    :	List[str]      ):
													a__:							int									=self.backend_tokenizer.decode

													def new_decode_method(*_a    :	Optional[Any]   ,							**_a    :	Any      ):
																				a__:							Any									=orig_decode_method(*_a   ,							**_a      )
																				a__:							Any									=text.replace(self.backend_tokenizer.model.end_of_word_suffix   ,							" "      ).strip()
																				return text

													a__:							str									=new_decode_method


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










from __future__ import annotations





def     __lowerCamelCase							(   __magic_name__						:	int    ):
							for r in range(1  ,			__magic_name__    ):
														a__:							List[str]									=[]
														for x in range(n - 1    ):
																					a__:							int									=pow(__magic_name__  ,			__magic_name__  ,			__magic_name__    )
																					if val in li:
																												break
																					li.append(__magic_name__    )
														else:
																					return r
							return None


if __name__ == "__main__":
		__UpperCAmelCase    	=  int(input('''Enter a prime number q: '''))
		__UpperCAmelCase    	=  find_primitive(q)
		if a is None:
				print(f"""Cannot find the primitive for the value: {a!r}""")
		else:
				__UpperCAmelCase    	=  int(input('''Enter private key of A: '''))
				__UpperCAmelCase    	=  pow(a, a_private, q)
				__UpperCAmelCase    	=  int(input('''Enter private key of B: '''))
				__UpperCAmelCase    	=  pow(a, b_private, q)

				__UpperCAmelCase    	=  pow(b_public, a_private, q)
				__UpperCAmelCase    	=  pow(a_public, b_private, q)

				print('''The key value generated by A is: ''', a_secret)
				print('''The key value generated by B is: ''', b_secret)





