





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

import numpy as np

from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
      from transformers.pipelines.conversational import Conversation


__UpperCAmelCase	:       Dict    	=							logging.get_logger(__name__)

__UpperCAmelCase	:       Dict    	=							{"vocab_file": "vocab.txt", "emoji_file": "emoji.json"}

__UpperCAmelCase	:       List[Any]    	=							{
    "vocab_file": {
        "abeja/gpt-neox-japanese-2.7b": "https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/vocab.txt",
    },
    "emoji_file": {
        "abeja/gpt-neox-japanese-2.7b": "https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/emoji.json",
    },
}

__UpperCAmelCase	:       Optional[int]    	=							{
    "abeja/gpt-neox-japanese-2.7b": 2_048,
}







def       A__							(   SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__)       ->   List[Any]:
  with open(SCREAMING_SNAKE_CASE__ , """r""" , encoding="""utf-8""") as f:
    __snake_case:						str			  =						json.loads(f.read())

  __snake_case:						Union[str, Any]			  =						collections.OrderedDict()
  __snake_case:						Dict			  =						collections.OrderedDict()
  __snake_case:						Tuple			  =						collections.OrderedDict()
  with open(SCREAMING_SNAKE_CASE__ , """r""" , encoding="""utf-8""") as f:
    __snake_case:						List[Any]			  =						f.readlines()
  __snake_case:						List[str]			  =						[[t.rstrip("""\n""")] if (t == """,""" or """,""" not in t) else t.rstrip("""\n""").split(""",""") for t in token]
  for idx, b in enumerate(SCREAMING_SNAKE_CASE__):
    __snake_case:						Tuple			  =						b
    __snake_case:						int			  =						idx
    for wd in b:
      __snake_case:						Union[str, Any]			  =						idx

  return vocab, raw_vocab, ids_to_tokens, emoji







class    __snake_case	(							__lowerCamelCase      ):





       '''simple docstring'''







       lowerCAmelCase__						=					VOCAB_FILES_NAMES
       lowerCAmelCase__						=					PRETRAINED_VOCAB_FILES_MAP
       lowerCAmelCase__						=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowerCAmelCase__						=					["""input_ids""", """attention_mask"""]




       def __init__(  self			:   Any							,    A			:   int							,    A			:   Any							,    A			:   Tuple="<|endoftext|>"							,    A			:   int="<|endoftext|>"							,    A			:   Any="<|startoftext|>"							,    A			:   str="<|endoftext|>"							,    A			:   Any=False							,    **A			:   List[Any]							,    ):
         super().__init__(
             unk_token=A							,    pad_token=A							,    bos_token=A							,    eos_token=A							,    do_clean_text=A							,    **A							,    )
         if not os.path.isfile(A		):
           raise ValueError(
               f'''Can\'t find a vocabulary file at path \'{vocab_file}\'. To load the vocabulary from a Google pretrained'''
               """ model use `tokenizer = GPTNeoXJapaneseokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`"""		)
         if not os.path.isfile(A		):
           raise ValueError(
               f'''Can\'t find a emoji file at path \'{emoji_file}\'. To load the emoji information from a Google'''
               """ pretrained model use `tokenizer = GPTNeoXJapaneseokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`"""		)
         __snake_case:						List[str]			  =						do_clean_text
         __snake_case  ,       __snake_case  ,       __snake_case  ,       __snake_case:						int			  =						load_vocab_and_emoji(A							,    A		)
         __snake_case:						Optional[int]			  =						SubWordJapaneseTokenizer(
             vocab=self.vocab							,    ids_to_tokens=self.ids_to_tokens							,    emoji=self.emoji		)




       @property
       def 							UpperCAmelCase__			(  self			:   Dict		):
         # self.vocab contains support for character fluctuation unique to Japanese, and has a large number of vocab
         return len(self.raw_vocab		)




       def 							UpperCAmelCase__			(  self			:   Union[str, Any]		):
         return dict(self.raw_vocab							,    **self.added_tokens_encoder		)




       def 							UpperCAmelCase__			(  self			:   int							,    A			:   Any		):
         return self.subword_tokenizer.tokenize(A							,    clean=self.do_clean_text		)




       def 							UpperCAmelCase__			(  self			:   Optional[Any]							,    A			:   Any		):
         return self.vocab.get(A							,    self.vocab.get(self.unk_token		)		)




       def 							UpperCAmelCase__			(  self			:   Optional[int]							,    A			:   List[str]		):
         return self.subword_tokenizer.convert_id_to_token(A		)




       def 							UpperCAmelCase__			(  self			:   Dict							,    A			:   Dict		):
         __snake_case:						Tuple			  =						"""""".join(A		).strip()
         return out_string




       def 							UpperCAmelCase__			(  self			:   Union[str, Any]							,    A			:   "Conversation"		):
         __snake_case:						Tuple			  =						[]
         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:
           __snake_case:						Any			  =						input_ids[-self.model_max_length :]
         return input_ids






       def 							UpperCAmelCase__			(  self			:   int							,    A			:   str							,    A			:   Optional[str] = None		):
         __snake_case:						Optional[int]			  =						0
         if os.path.isdir(A		):
           __snake_case:						Optional[int]			  =						os.path.join(
               A							,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]		)
           __snake_case:						Optional[Any]			  =						os.path.join(
               A							,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""emoji_file"""]		)
         else:
           __snake_case:						str			  =						(
               (filename_prefix + """-""" if filename_prefix else """""") + save_directory + VOCAB_FILES_NAMES["""vocab_file"""]
           )
           __snake_case:						str			  =						(
               (filename_prefix + """-""" if filename_prefix else """""") + save_directory + VOCAB_FILES_NAMES["""emoji_file"""]
           )
         with open(A							,    """w"""							,    encoding="""utf-8"""		) as writer:
           for token_index, token in self.ids_to_tokens.items():
             if index != token_index:
               logger.warning(
                   f'''Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive.'''
                   """ Please check that the vocabulary is not corrupted!"""		)
               __snake_case:						List[Any]			  =						token_index
             writer.write(""",""".join(A		) + """\n"""		)
             index += 1
         with open(A							,    """w"""							,    encoding="""utf-8"""		) as writer:
           json.dump(self.emoji							,    A		)
         return vocab_file, emoji_file







class    __snake_case	(							__lowerCamelCase      ):





       '''simple docstring'''







       def __init__(  self			:   Union[str, Any]							,    A			:   Dict							,    A			:   Optional[int]							,    A			:   str		):
         __snake_case:						List[Any]			  =						vocab  # same as swe
         __snake_case:						Tuple			  =						ids_to_tokens  # same as bpe
         __snake_case:						Tuple			  =						emoji
         __snake_case:						Optional[Any]			  =						np.max([len(A		) for w in self.vocab.keys()]		)
         __snake_case:						Optional[int]			  =						re.compile(r"""(https?|ftp)(:\/\/[-_\.!~*\'()a-zA-Z0-9;\/?:\@&=\+$,%#]+)"""		)
         __snake_case:						List[Any]			  =						re.compile(r"""[A-Za-z0-9\._+]*@[\-_0-9A-Za-z]+(\.[A-Za-z]+)*"""		)
         __snake_case:						List[str]			  =						re.compile(r"""[\(]{0,1}[0-9]{2,4}[\)\-\(]{0,1}[0-9]{2,4}[\)\-]{0,1}[0-9]{3,4}"""		)
         __snake_case:						Tuple			  =						re.compile(
             r"""([12]\d{3}[/\-年])*(0?[1-9]|1[0-2])[/\-月]((0?[1-9]|[12][0-9]|3[01])日?)*(\d{1,2}|:|\d{1,2}時|\d{1,2}分|\(日\)|\(月\)|\(火\)|\(水\)|\(木\)|\(金\)|\(土\)|㈰|㈪|㈫|㈬|㈭|㈮|㈯)*"""		)
         __snake_case:						str			  =						re.compile(
             r"""(明治|大正|昭和|平成|令和|㍾|㍽|㍼|㍻|\u32ff)\d{1,2}年(0?[1-9]|1[0-2])月(0?[1-9]|[12][0-9]|3[01])日(\d{1,2}|:|\d{1,2}時|\d{1,2}分|\(日\)|\(月\)|\(火\)|\(水\)|\(木\)|\(金\)|\(土\)|㈰|㈪|㈫|㈬|㈭|㈮|㈯)*"""		)
         __snake_case:						Optional[Any]			  =						re.compile(
             r"""((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*億)*((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*万)*((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*千)*(0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*(千円|万円|千万円|円|千ドル|万ドル|千万ドル|ドル|千ユーロ|万ユーロ|千万ユーロ|ユーロ)+(\(税込\)|\(税抜\)|\+tax)*"""		)
         __snake_case:						Union[str, Any]			  =						"""─━│┃┄┅┆┇┈┉┊┋┌┍┎┏┐┑┒┓└┕┖┗┘┙┚┛├┝┞┟┠┡┢┣┤┥┦┧┨┩┪┫┬┭┮┯┰┱┲┳┴┵┶┷┸┹┺┻┼┽┾┿╀╁╂╃╄╅╆╇╈╉╊╋╌╍╎╏═║╒╓╔╕╖╗╘╙╚╛╜╝╞╟╠╡╢╣╤╥╦╧╨╩╪╫╬╭╮╯╰╱╲╳╴╵╶╷╸╹╺╻╼╽╾╿"""
         __snake_case:						List[str]			  =						"""▀▁▂▃▄▅▆▇█▉▊▋▌▍▎▏▐░▒▓▔▕▖▗▘▙▚▛▜▝▞▟"""
         __snake_case:						str			  =						str.maketrans({k: """<BLOCK>""" for k in keisen + blocks}		)




       def __len__(  self			:   Optional[Any]		):
         return len(self.ids_to_tokens		)




       def 							UpperCAmelCase__			(  self			:   str							,    A			:   List[Any]		):
         __snake_case:						str			  =						self.content_repattera.sub("""<URL>"""							,    A		)
         __snake_case:						Dict			  =						self.content_repattera.sub("""<EMAIL>"""							,    A		)
         __snake_case:						Optional[Any]			  =						self.content_repattera.sub("""<TEL>"""							,    A		)
         __snake_case:						List[str]			  =						self.content_repattera.sub("""<DATE>"""							,    A		)
         __snake_case:						Tuple			  =						self.content_repattera.sub("""<DATE>"""							,    A		)
         __snake_case:						List[str]			  =						self.content_repattera.sub("""<PRICE>"""							,    A		)
         __snake_case:						Union[str, Any]			  =						content.translate(self.content_transa		)
         while "<BLOCK><BLOCK>" in content:
           __snake_case:						Optional[Any]			  =						content.replace("""<BLOCK><BLOCK>"""							,    """<BLOCK>"""		)
         return content




       def 							UpperCAmelCase__			(  self			:   Optional[int]							,    A			:   Optional[int]							,    A			:   str=False		):
         __snake_case:						Optional[Any]			  =						text.replace(""" """							,    """<SP>"""		)
         __snake_case:						Optional[Any]			  =						text.replace("""　"""							,    """<SP>"""		)
         __snake_case:						Optional[int]			  =						text.replace("""\r\n"""							,    """<BR>"""		)
         __snake_case:						List[Any]			  =						text.replace("""\n"""							,    """<BR>"""		)
         __snake_case:						List[Any]			  =						text.replace("""\r"""							,    """<BR>"""		)
         __snake_case:						List[Any]			  =						text.replace("""\t"""							,    """<TAB>"""		)
         __snake_case:						Tuple			  =						text.replace("""—"""							,    """ー"""		)
         __snake_case:						Any			  =						text.replace("""−"""							,    """ー"""		)
         for k, v in self.emoji["emoji"].items():
           if k in text:
             __snake_case:						List[str]			  =						text.replace(A							,    A		)
         if clean:
           __snake_case:						List[str]			  =						self.clean_text(A		)

         def check_simbol(A			:   List[str]		):
           __snake_case:						List[str]			  =						x.encode()
           if len(A		) == 1 and len(A		) == 2:
             __snake_case:						Union[str, Any]			  =						(int(e[0]		) << 8) + int(e[1]		)
             if (
                 (c >= 0xc2_a1 and c <= 0xc2_bf)
                 or (c >= 0xc7_80 and c <= 0xc7_83)
                 or (c >= 0xca_b9 and c <= 0xcb_bf)
                 or (c >= 0xcc_80 and c <= 0xcd_a2)
             ):
               return True
           return False

         def checkuae(A			:   List[str]		):
           __snake_case:						int			  =						x.encode()
           if len(A		) == 1 and len(A		) == 3:
             __snake_case:						Dict			  =						(int(e[0]		) << 16) + (int(e[1]		) << 8) + int(e[2]		)
             if c >= 0xe2_80_80 and c <= 0xe2_b0_7f:
               return True
           return False

         __snake_case:						Tuple			  =						0
         __snake_case:						Union[str, Any]			  =						[]
         while pos < len(A		):
           __snake_case:						Optional[Any]			  =						min(len(A		)							,    pos + self.maxlen + 1		) if text[pos] == """<""" else pos + 3
           __snake_case:						List[str]			  =						[]  # (token_id, token, pos)
           for e in range(A							,    A							,    -1		):
             __snake_case:						str			  =						text[pos:e]
             if wd in self.vocab:
               if wd[0] == "<" and len(A		) > 2:
                 __snake_case:						Optional[Any]			  =						[(self.vocab[wd], wd, e)]
                 break
               else:
                 candidates.append((self.vocab[wd], wd, e)		)
           if len(A		) > 0:
             # the smallest token_id is adopted
             __snake_case  ,       __snake_case  ,       __snake_case:						Tuple			  =						sorted(A							,    key=lambda A		: x[0]		)[0]
             result.append(A		)
             __snake_case:						Optional[int]			  =						e
           else:
             __snake_case:						Any			  =						pos + 1
             __snake_case:						Any			  =						text[pos:end]
             if check_simbol(A		):
               result.append("""<KIGOU>"""		)
             elif checkuae(A		):
               result.append("""<U2000U2BFF>"""		)
             else:
               for i in wd.encode("""utf-8"""		):
                 result.append("""<|byte%d|>""" % i		)
             __snake_case:						Tuple			  =						end
         return result






       def 							UpperCAmelCase__			(  self			:   List[Any]							,    A			:   List[str]							,    A			:   Tuple="\n"		):
         __snake_case:						List[str]			  =						[]
         __snake_case:						Union[str, Any]			  =						[]
         __snake_case:						Tuple			  =						self.ids_to_tokens[index][0]
         if word[:6] == "<|byte" and word[-2:] == "|>":
           byte_tokens.append(int(word[6:-2]		)		)
         else:
           if len(A		) > 0:
             words.append(bytearray(A		).decode("""utf-8"""							,    errors="""replace"""		)		)
             __snake_case:						Dict			  =						[]
           if word[:7] == "<|emoji" and word[-2:] == "|>":
             words.append(self.emoji["""emoji_inv"""][word]		)
           elif word == "<SP>":
             words.append(""" """		)
           elif word == "<BR>":
             words.append(A		)
           elif word == "<TAB>":
             words.append("""\t"""		)
           elif word == "<BLOCK>":
             words.append("""▀"""		)
           elif word == "<KIGOU>":
             words.append("""ǀ"""		)
           elif word == "<U2000U2BFF>":
             words.append("""‖"""		)
           else:
             words.append(A		)
         if len(A		) > 0:
           words.append(bytearray(A		).decode("""utf-8"""							,    errors="""replace"""		)		)
         __snake_case:						List[Any]			  =						"""""".join(A		)
         return text













import math

import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute







def       A__							(   SCREAMING_SNAKE_CASE__ = 3)       ->   qiskit.result.counts.Counts:
  if isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__):
    raise TypeError("""number of qubits must be a integer.""")
  if number_of_qubits <= 0:
    raise ValueError("""number of qubits must be > 0.""")
  if math.floor(SCREAMING_SNAKE_CASE__) != number_of_qubits:
    raise ValueError("""number of qubits must be exact integer.""")
  if number_of_qubits > 10:
    raise ValueError("""number of qubits too large to simulate(>10).""")

  __snake_case:						int			  =						QuantumRegister(SCREAMING_SNAKE_CASE__ , """qr""")
  __snake_case:						List[str]			  =						ClassicalRegister(SCREAMING_SNAKE_CASE__ , """cr""")

  __snake_case:						Optional[Any]			  =						QuantumCircuit(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__)

  __snake_case:						Tuple			  =						number_of_qubits

  for i in range(SCREAMING_SNAKE_CASE__):
    quantum_circuit.h(number_of_qubits - i - 1)
    counter -= 1
    for j in range(SCREAMING_SNAKE_CASE__):
      quantum_circuit.cp(np.pi / 2 ** (counter - j) , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__)

  for k in range(number_of_qubits // 2):
    quantum_circuit.swap(SCREAMING_SNAKE_CASE__ , number_of_qubits - k - 1)

  # measure all the qubits
  quantum_circuit.measure(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__)
  # simulate with 10000 shots
  __snake_case:						Union[str, Any]			  =						Aer.get_backend("""qasm_simulator""")
  __snake_case:						Optional[Any]			  =						execute(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , shots=1_0000)

  return job.result().get_counts(SCREAMING_SNAKE_CASE__)


if __name__ == "__main__":
      print(
          f'Total count for quantum fourier transform state is: \
    {quantum_fourier_transform(3)}'
      )






