"""simple docstring"""







import json
import os
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
       from transformers.pipelines.conversational import Conversation

lowerCamelCase      : List[str]       =logging.get_logger(__name__)

lowerCamelCase      : str       ={"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt"""}

lowerCamelCase      : List[str]       ={
    """vocab_file""": {
        """microsoft/deberta-base""": """https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json""",
        """microsoft/deberta-large""": """https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json""",
        """microsoft/deberta-xlarge""": """https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json""",
        """microsoft/deberta-base-mnli""": """https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json""",
        """microsoft/deberta-large-mnli""": """https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json""",
        """microsoft/deberta-xlarge-mnli""": (
            """https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json"""
        ),
    },
    """merges_file""": {
        """microsoft/deberta-base""": """https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt""",
        """microsoft/deberta-large""": """https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt""",
        """microsoft/deberta-xlarge""": """https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt""",
        """microsoft/deberta-base-mnli""": """https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt""",
        """microsoft/deberta-large-mnli""": """https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt""",
        """microsoft/deberta-xlarge-mnli""": (
            """https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt"""
        ),
    },
}

lowerCamelCase      : Optional[int]       ={
    """microsoft/deberta-base""": 5_12,
    """microsoft/deberta-large""": 5_12,
    """microsoft/deberta-xlarge""": 5_12,
    """microsoft/deberta-base-mnli""": 5_12,
    """microsoft/deberta-large-mnli""": 5_12,
    """microsoft/deberta-xlarge-mnli""": 5_12,
}

lowerCamelCase      : Tuple       ={
    """microsoft/deberta-base""": {"""do_lower_case""": False},
    """microsoft/deberta-large""": {"""do_lower_case""": False},
}




def 						_lowercase				(  )    ->     Optional[int]:







     '''simple docstring'''


     __A					:					List[str]								=		(
         list(range(ord('!'						)  ,       ord('~'						) + 1						)						) + list(range(ord('¡'						)  ,       ord('¬'						) + 1						)						) + list(range(ord('®'						)  ,       ord('ÿ'						) + 1						)						)
     )
     __A					:					str								=		bs[:]
     __A					:					Optional[int]								=		0
     for b in range(2**8						):
          if b not in bs:
               bs.append(lowerCAmelCase_						)
               cs.append(2**8 + n						)
               n += 1
     __A					:					Optional[int]								=		[chr(lowerCAmelCase_						) for n in cs]
     return dict(zip(lowerCAmelCase_  ,       lowerCAmelCase_						)						)




def 						_lowercase				(  _SCREAMING_SNAKE_CASE				:				Dict						)    ->     Optional[Any]:







     '''simple docstring'''


     __A					:					str								=		set()
     __A					:					Any								=		word[0]
     for char in word[1:]:
          pairs.add((prev_char, char)						)
          __A					:					List[Any]								=		char
     return pairs






class 							__snake_case(					_lowerCamelCase	):


    '''simple docstring'''





    _UpperCAmelCase       =			VOCAB_FILES_NAMES
    _UpperCAmelCase       =			PRETRAINED_VOCAB_FILES_MAP
    _UpperCAmelCase       =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    _UpperCAmelCase       =			["input_ids", "attention_mask", "token_type_ids"]
    def __init__(  self					,       __lowerCamelCase					,       __lowerCamelCase					,       __lowerCamelCase="replace"					,       __lowerCamelCase="[CLS]"					,       __lowerCamelCase="[SEP]"					,       __lowerCamelCase="[SEP]"					,       __lowerCamelCase="[CLS]"					,       __lowerCamelCase="[UNK]"					,       __lowerCamelCase="[PAD]"					,       __lowerCamelCase="[MASK]"					,       __lowerCamelCase=False					,       __lowerCamelCase=False					,       **__lowerCamelCase					,       ):




         '''simple docstring'''



         __A					:					Dict								=		AddedToken(a_					,       lstrip=a_					,       rstrip=a_	) if isinstance(a_					,       a_	) else bos_token
         __A					:					Optional[int]								=		AddedToken(a_					,       lstrip=a_					,       rstrip=a_	) if isinstance(a_					,       a_	) else eos_token
         __A					:					List[str]								=		AddedToken(a_					,       lstrip=a_					,       rstrip=a_	) if isinstance(a_					,       a_	) else sep_token
         __A					:					Tuple								=		AddedToken(a_					,       lstrip=a_					,       rstrip=a_	) if isinstance(a_					,       a_	) else cls_token
         __A					:					List[str]								=		AddedToken(a_					,       lstrip=a_					,       rstrip=a_	) if isinstance(a_					,       a_	) else unk_token
         __A					:					Dict								=		AddedToken(a_					,       lstrip=a_					,       rstrip=a_	) if isinstance(a_					,       a_	) else pad_token

         # Mask token behave like a normal word, i.e. include the space before it
         __A					:					List[str]								=		AddedToken(a_					,       lstrip=a_					,       rstrip=a_	) if isinstance(a_					,       a_	) else mask_token

         super().__init__(
             errors=a_					,       bos_token=a_					,       eos_token=a_					,       unk_token=a_					,       sep_token=a_					,       cls_token=a_					,       pad_token=a_					,       mask_token=a_					,       add_prefix_space=a_					,       add_bos_token=a_					,       **a_					,       )
         __A					:					Any								=		add_bos_token

         with open(a_					,       encoding='utf-8'	) as vocab_handle:
              __A					:					Optional[int]								=		json.load(a_	)
         __A					:					Any								=		{v: k for k, v in self.encoder.items()}
         __A					:					str								=		errors  # how to handle errors in decoding
         __A					:					Any								=		bytes_to_unicode()
         __A					:					List[Any]								=		{v: k for k, v in self.byte_encoder.items()}
         with open(a_					,       encoding='utf-8'	) as merges_handle:
              __A					:					int								=		merges_handle.read().split('\n'	)[1:-1]
         __A					:					str								=		[tuple(merge.split()	) for merge in bpe_merges]
         __A					:					str								=		dict(zip(a_					,       range(len(a_	)	)	)	)
         __A					:					str								=		{}
         __A					:					List[str]								=		add_prefix_space

         # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
         __A					:					List[Any]								=		re.compile(R'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'	)
    @property
    # Copied from transformers.models.gpt2.tokenization_gpt2.GPT2Tokenizer.vocab_size
    def 						_a							(  self	):




         '''simple docstring'''



         return len(self.encoder	)
    def 						_a							(  self	):




         '''simple docstring'''



         return dict(self.encoder					,       **self.added_tokens_encoder	)
    def 						_a							(  self					,       __lowerCamelCase	):




         '''simple docstring'''



         if token in self.cache:
              return self.cache[token]
         __A					:					Any								=		tuple(a_	)
         __A					:					Tuple								=		get_pairs(a_	)

         if not pairs:
              return token

         while True:
              __A					:					List[Any]								=		min(a_					,       key=lambda __lowerCamelCase	: self.bpe_ranks.get(a_					,       float('inf'	)	)	)
              if bigram not in self.bpe_ranks:
                   break
              __A					:					List[str]								=		bigram
              __A					:					str								=		[]
              __A					:					int								=		0
              while i < len(a_	):
                   try:
                        __A					:					Tuple								=		word.index(a_					,       a_	)
                   except ValueError:
                        new_word.extend(word[i:]	)
                        break
                   else:
                        new_word.extend(word[i:j]	)
                        __A					:					Tuple								=		j

                   if word[i] == first and i < len(a_	) - 1 and word[i + 1] == second:
                        new_word.append(first + second	)
                        i += 2
                   else:
                        new_word.append(word[i]	)
                        i += 1
              __A					:					Optional[int]								=		tuple(a_	)
              __A					:					Any								=		new_word
              if len(a_	) == 1:
                   break
              else:
                   __A					:					Any								=		get_pairs(a_	)
         __A					:					List[str]								=		""" """.join(a_	)
         __A					:					Dict								=		word
         return word
    def 						_a							(  self					,       __lowerCamelCase					,       __lowerCamelCase = None	):




         '''simple docstring'''



         if token_ids_a is None:
              return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
         __A					:					Optional[int]								=		[self.cls_token_id]
         __A					:					str								=		[self.sep_token_id]
         return cls + token_ids_a + sep + token_ids_a + sep
    def 						_a							(  self					,       __lowerCamelCase					,       __lowerCamelCase = None					,       __lowerCamelCase = False	):




         '''simple docstring'''



         if already_has_special_tokens:
              return super().get_special_tokens_mask(
                  token_ids_a=a_					,       token_ids_a=a_					,       already_has_special_tokens=a_	)

         if token_ids_a is None:
              return [1] + ([0] * len(a_	)) + [1]
         return [1] + ([0] * len(a_	)) + [1] + ([0] * len(a_	)) + [1]
    def 						_a							(  self					,       __lowerCamelCase					,       __lowerCamelCase = None	):




         '''simple docstring'''



         __A					:					List[Any]								=		[self.sep_token_id]
         __A					:					Tuple								=		[self.cls_token_id]

         if token_ids_a is None:
              return len(cls + token_ids_a + sep	) * [0]
         return len(cls + token_ids_a + sep	) * [0] + len(token_ids_a + sep	) * [1]
    def 						_a							(  self					,       __lowerCamelCase	):




         '''simple docstring'''



         __A					:					Optional[Any]								=		[]
         for token in re.findall(self.pat					,       a_	):
              __A					:					List[Any]								=		"""""".join(
                  self.byte_encoder[b] for b in token.encode('utf-8'	)	)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
              bpe_tokens.extend(bpe_token for bpe_token in self.bpe(a_	).split(' '	)	)
         return bpe_tokens
    def 						_a							(  self					,       __lowerCamelCase	):




         '''simple docstring'''



         return self.encoder.get(a_					,       self.encoder.get(self.unk_token	)	)
    def 						_a							(  self					,       __lowerCamelCase	):




         '''simple docstring'''



         return self.decoder.get(a_	)
    def 						_a							(  self					,       __lowerCamelCase	):




         '''simple docstring'''



         __A					:					Optional[Any]								=		"""""".join(a_	)
         __A					:					Union[str, Any]								=		bytearray([self.byte_decoder[c] for c in text]	).decode('utf-8'					,       errors=self.errors	)
         return text
    def 						_a							(  self					,       __lowerCamelCase					,       __lowerCamelCase = None	):




         '''simple docstring'''



         if not os.path.isdir(a_	):
              logger.error(F'Vocabulary path ({save_directory}) should be a directory'	)
              return
         __A					:					Union[str, Any]								=		os.path.join(
             a_					,       (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)
         __A					:					Tuple								=		os.path.join(
             a_					,       (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']	)

         with open(a_					,       'w'					,       encoding='utf-8'	) as f:
              f.write(json.dumps(self.encoder					,       indent=2					,       sort_keys=a_					,       ensure_ascii=a_	) + '\n'	)

         __A					:					List[str]								=		0
         with open(a_					,       'w'					,       encoding='utf-8'	) as writer:
              writer.write('#version: 0.2\n'	)
              for bpe_tokens, token_index in sorted(self.bpe_ranks.items()					,       key=lambda __lowerCamelCase	: kv[1]	):
                   if index != token_index:
                        logger.warning(
                            F'Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'
                            ' Please check that the tokenizer is not corrupted!'	)
                        __A					:					List[Any]								=		token_index
                   writer.write(' '.join(a_	) + '\n'	)
                   index += 1

         return vocab_file, merge_file
    def 						_a							(  self					,       __lowerCamelCase					,       __lowerCamelCase=False					,       **__lowerCamelCase	):




         '''simple docstring'''



         __A					:					int								=		kwargs.pop('add_prefix_space'					,       self.add_prefix_space	)
         if (is_split_into_words or add_prefix_space) and (len(a_	) > 0 and not text[0].isspace()):
              __A					:					Any								=		""" """ + text
         return (text, kwargs)

    def 						_a							(  self					,       __lowerCamelCase	):




         '''simple docstring'''



         __A					:					str								=		[]
         for is_user, text in conversation.iter_texts():
              input_ids.extend(self.encode(a_					,       add_special_tokens=a_	) + [self.eos_token_id]	)
         if len(a_	) > self.model_max_length:
              __A					:					List[Any]								=		input_ids[-self.model_max_length :]
         return input_ids








'''simple docstring'''






import qiskit
from qiskit.providers import Backend




def        snake_case_   (	lowerCAmelCase_			,  lowerCAmelCase_						)->						tuple[qiskit.QuantumCircuit, str, str]:





       '''simple docstring'''


       _UpperCAmelCase	,_UpperCAmelCase    :		Optional[Any]     	=					bin(lowerCAmelCase_						)[2:], bin(lowerCAmelCase_						)[2:]  # Remove leading '0b'

       # Ensure that both strings are of the same length
       if len(lowerCAmelCase_						) > len(lowerCAmelCase_						):
              _UpperCAmelCase    :		str     	=					y.zfill(len(lowerCAmelCase_						)						)
       else:
              _UpperCAmelCase    :		int     	=					x.zfill(len(lowerCAmelCase_						)						)

       # We need (3 * number of bits in the larger number)+1 qBits
       # The second parameter is the number of classical registers, to measure the result
       _UpperCAmelCase    :		Any     	=					qiskit.QuantumCircuit((len(lowerCAmelCase_						) * 3) + 1			,  len(lowerCAmelCase_						) + 1						)

       # We are essentially "not-ing" the bits that are 1
       # Reversed because it's easier to perform ops on more significant bits
       for i in range(len(lowerCAmelCase_						)						):
              if x[::-1][i] == "1":
                     circuit.x(lowerCAmelCase_						)
       for j in range(len(lowerCAmelCase_						)						):
              if y[::-1][j] == "1":
                     circuit.x(len(lowerCAmelCase_						) + j						)

       return circuit, x, y




def        snake_case_   (	lowerCAmelCase_			,  lowerCAmelCase_			,  lowerCAmelCase_			,  lowerCAmelCase_			,  lowerCAmelCase_			,  )->						Dict:





       '''simple docstring'''


       circuit.ccx(lowerCAmelCase_			,  lowerCAmelCase_			,  lowerCAmelCase_						)
       circuit.cx(lowerCAmelCase_			,  lowerCAmelCase_						)
       circuit.ccx(lowerCAmelCase_			,  lowerCAmelCase_			,  lowerCAmelCase_						)
       circuit.cx(lowerCAmelCase_			,  lowerCAmelCase_						)
       circuit.cx(lowerCAmelCase_			,  lowerCAmelCase_						)




def        snake_case_   (	lowerCAmelCase_			,  lowerCAmelCase_			,  lowerCAmelCase_ = qiskit.Aer.get_backend("""aer_simulator"""						)			,  )->						int:





       '''simple docstring'''


       if vala < 0 or vala < 0:
              raise ValueError("""Both Integers must be positive!"""						)

       # Store the Integers
       _UpperCAmelCase	,_UpperCAmelCase	,_UpperCAmelCase    :		Union[str, Any]     	=					store_two_classics(lowerCAmelCase_			,  lowerCAmelCase_						)
       for i in range(len(lowerCAmelCase_						)						):
              full_adder(lowerCAmelCase_			,  lowerCAmelCase_			,  len(lowerCAmelCase_						) + i			,  len(lowerCAmelCase_						) + len(lowerCAmelCase_						) + i			,  len(lowerCAmelCase_						) + len(lowerCAmelCase_						) + i + 1						)
              circuit.barrier()  # Optional, just for aesthetics

       # Measure the resultant qBits
       for i in range(len(lowerCAmelCase_						) + 1						):
              circuit.measure([(len(lowerCAmelCase_						) * 2) + i]			,  [i]						)

       _UpperCAmelCase    :		Optional[int]     	=					qiskit.execute(lowerCAmelCase_			,  lowerCAmelCase_			,  shots=1						).result()

       # The result is in binary. Convert it back to int
       return int(list(res.get_counts()						)[0]			,  2						)


if __name__ == "__main__":
   import doctest

   doctest.testmod()



