






import json
import os
from typing import Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


snake_case    				=		logging.get_logger(__name__)

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

snake_case    				=		{
    "vocab_file": {"ctrl": "https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-vocab.json"},
    "merges_file": {"ctrl": "https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-merges.txt"},
}

snake_case    				=		{
    "ctrl": 256,
}

snake_case    				=		{
    "Pregnancy": 168_629,
    "Christianity": 7_675,
    "Explain": 106_423,
    "Fitness": 63_440,
    "Saving": 63_163,
    "Ask": 27_171,
    "Ass": 95_985,
    "Joke": 163_509,
    "Questions": 45_622,
    "Thoughts": 49_605,
    "Retail": 52_342,
    "Feminism": 164_338,
    "Writing": 11_992,
    "Atheism": 192_263,
    "Netflix": 48_616,
    "Computing": 39_639,
    "Opinion": 43_213,
    "Alone": 44_967,
    "Funny": 58_917,
    "Gaming": 40_358,
    "Human": 4_088,
    "India": 1_331,
    "Joker": 77_138,
    "Diet": 36_206,
    "Legal": 11_859,
    "Norman": 4_939,
    "Tip": 72_689,
    "Weight": 52_343,
    "Movies": 46_273,
    "Running": 23_425,
    "Science": 2_090,
    "Horror": 37_793,
    "Confession": 60_572,
    "Finance": 12_250,
    "Politics": 16_360,
    "Scary": 191_985,
    "Support": 12_654,
    "Technologies": 32_516,
    "Teenage": 66_160,
    "Event": 32_769,
    "Learned": 67_460,
    "Notion": 182_770,
    "Wikipedia": 37_583,
    "Books": 6_665,
    "Extract": 76_050,
    "Confessions": 102_701,
    "Conspiracy": 75_932,
    "Links": 63_674,
    "Narcissus": 150_425,
    "Relationship": 54_766,
    "Relationships": 134_796,
    "Reviews": 41_671,
    "News": 4_256,
    "Translation": 26_820,
    "multilingual": 128_406,
}


def   lowerCamelCase__			(     lowercase				):

  """simple docstring"""






  SCREAMING_SNAKE_CASE       :      Optional[Any]							=    set()
  SCREAMING_SNAKE_CASE       :      int							=    word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)				)
    SCREAMING_SNAKE_CASE       :      Optional[int]							=    char

  SCREAMING_SNAKE_CASE       :      List[Any]							=    set(lowerCamelCase__				)
  return pairs


class  SCREAMING_SNAKE_CASE			(			lowerCAmelCase					):
  '''simple docstring'''


  UpperCamelCase_							:		List[Any]			=	VOCAB_FILES_NAMES
  UpperCamelCase_							:		Optional[int]			=	PRETRAINED_VOCAB_FILES_MAP
  UpperCamelCase_							:		Optional[Any]			=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  UpperCamelCase_							:		Tuple			=	CONTROL_CODES


  def __init__(				self       :	List[Any]					, UpperCAmelCase_       :	int					, UpperCAmelCase_       :	List[str]					, UpperCAmelCase_       :	int="<unk>"					, **UpperCAmelCase_       :	Any      ):
    super().__init__(unk_token=UpperCamelCase_					, **UpperCamelCase_      )

    with open(UpperCamelCase_					, encoding="utf-8"      ) as vocab_handle:
      SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    json.load(UpperCamelCase_      )
    SCREAMING_SNAKE_CASE       :      Optional[int]							=    {v: k for k, v in self.encoder.items()}
    with open(UpperCamelCase_					, encoding="utf-8"      ) as merges_handle:
      SCREAMING_SNAKE_CASE       :      List[Any]							=    merges_handle.read().split("\n"      )[1:-1]
    SCREAMING_SNAKE_CASE       :      Optional[int]							=    [tuple(merge.split()      ) for merge in merges]
    SCREAMING_SNAKE_CASE       :      str							=    dict(zip(UpperCamelCase_					, range(len(UpperCamelCase_      )      )      )      )
    SCREAMING_SNAKE_CASE       :      List[Any]							=    {}


  @property
  def 				_A       (				self       :	Any      ):
    return len(self.encoder      )


  def 				_A       (				self       :	str      ):
    return dict(self.encoder					, **self.added_tokens_encoder      )


  def 				_A       (				self       :	Dict					, UpperCAmelCase_       :	Any      ):
    if token in self.cache:
      return self.cache[token]
    SCREAMING_SNAKE_CASE       :      List[Any]							=    tuple(UpperCamelCase_      )
    SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    tuple(list(word[:-1]      ) + [word[-1] + "</w>"]      )
    SCREAMING_SNAKE_CASE       :      Tuple							=    get_pairs(UpperCamelCase_      )

    if not pairs:
      return token

    while True:
      SCREAMING_SNAKE_CASE       :      int							=    min(UpperCamelCase_					, key=lambda UpperCAmelCase_      : self.bpe_ranks.get(UpperCamelCase_					, float("inf"      )      )      )
      if bigram not in self.bpe_ranks:
        break
      SCREAMING_SNAKE_CASE       :      Optional[int]							=    bigram
      SCREAMING_SNAKE_CASE       :      int							=    []
      SCREAMING_SNAKE_CASE       :      Optional[Any]							=    0
      while i < len(UpperCamelCase_      ):
        try:
          SCREAMING_SNAKE_CASE       :      Any							=    word.index(UpperCamelCase_					, UpperCamelCase_      )
        except ValueError:
          new_word.extend(word[i:]      )
          break
        else:
          new_word.extend(word[i:j]      )
          SCREAMING_SNAKE_CASE       :      Optional[Any]							=    j

        if word[i] == first and i < len(UpperCamelCase_      ) - 1 and word[i + 1] == second:
          new_word.append(first + second      )
          i += 2
        else:
          new_word.append(word[i]      )
          i += 1
      SCREAMING_SNAKE_CASE       :      Dict							=    tuple(UpperCamelCase_      )
      SCREAMING_SNAKE_CASE       :      int							=    new_word
      if len(UpperCamelCase_      ) == 1:
        break
      else:
        SCREAMING_SNAKE_CASE       :      str							=    get_pairs(UpperCamelCase_      )
    SCREAMING_SNAKE_CASE       :      Any							=    "@@ ".join(UpperCamelCase_      )
    SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    word[:-4]
    SCREAMING_SNAKE_CASE       :      Optional[Any]							=    word
    return word


  def 				_A       (				self       :	Any					, UpperCAmelCase_       :	List[str]      ):
    SCREAMING_SNAKE_CASE       :      int							=    []

    SCREAMING_SNAKE_CASE       :      str							=    re.findall(r"\S+\n?"					, UpperCamelCase_      )

    for token in words:
      split_tokens.extend(list(self.bpe(UpperCamelCase_      ).split(" "      )      )      )
    return split_tokens


  def 				_A       (				self       :	Tuple					, UpperCAmelCase_       :	List[Any]      ):
    return self.encoder.get(UpperCamelCase_					, self.encoder.get(self.unk_token      )      )


  def 				_A       (				self       :	int					, UpperCAmelCase_       :	Optional[Any]      ):
    return self.decoder.get(UpperCamelCase_					, self.unk_token      )


  def 				_A       (				self       :	Any					, UpperCAmelCase_       :	Optional[int]      ):
    SCREAMING_SNAKE_CASE       :      List[Any]							=    " ".join(UpperCamelCase_      ).replace("@@ "					, ""      ).strip()
    return out_string






  def 				_A       (				self       :	Dict					, UpperCAmelCase_       :	str					, UpperCAmelCase_       :	str = None      ):
    if not os.path.isdir(UpperCamelCase_      ):
      logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''      )
      return
    SCREAMING_SNAKE_CASE       :      int							=    os.path.join(
        UpperCamelCase_					, (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]      )
    SCREAMING_SNAKE_CASE       :      List[Any]							=    os.path.join(
        UpperCamelCase_					, (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]      )

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

    SCREAMING_SNAKE_CASE       :      List[str]							=    0
    with open(UpperCamelCase_					, "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 UpperCAmelCase_      : 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!"      )
          SCREAMING_SNAKE_CASE       :      List[str]							=    token_index
        writer.write(" ".join(UpperCamelCase_      ) + "\n"      )
        index += 1

    return vocab_file, merge_file

  # def decode(self, token_ids, skip_special_tokens=False, clean_up_tokenization_spaces=True):
  #     filtered_tokens = ' '.join(self.convert_ids_to_tokens(token_ids, skip_special_tokens=skip_special_tokens))
  #     tokens_generated_so_far = re.sub('(@@ )', '', string=filtered_tokens)
  #     tokens_generated_so_far = re.sub('(@@ ?$)', '', string=tokens_generated_so_far)
  #     return ''.join(tokens_generated_so_far)














import qiskit


def   lowerCamelCase__			(     lowercase						,     lowercase				):

  """simple docstring"""






  SCREAMING_SNAKE_CASE       :      List[str]							=    qiskit.Aer.get_backend("aer_simulator"				)

  # Create a Quantum Circuit acting on the q register
  SCREAMING_SNAKE_CASE       :      Dict							=    qiskit.QuantumCircuit(lowercase						,     lowercase				)

  # Map the quantum measurement to the classical bits
  circuit.measure([0]						,     [0]				)

  # Execute the circuit on the simulator
  SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    qiskit.execute(lowercase						,     lowercase						,     shots=1000				)

  # Return the histogram data of the results of the experiment.
  return job.result().get_counts(lowercase				)


if __name__ == "__main__":
   print(F"""Total count for various states are: {single_qubit_measure(1, 1)}""")






