




"""simple docstring"""

import qiskit

def 						lowercase_					(						_UpperCAmelCase     ,					_UpperCAmelCase		):




	"""simple docstring"""






	A_     : Any		      =						qiskit.Aer.get_backend('''aer_simulator'''		)

	# Create a Quantum Circuit acting on the q register
	A_     : List[str]		      =						qiskit.QuantumCircuit(_lowerCamelCase     ,					_lowerCamelCase		)

	# Apply X (NOT) Gate to Qubits 0 & 1
	circuit.x(0		)
	circuit.x(1		)

	# Map the quantum measurement to the classical bits
	circuit.measure([0, 1]     ,					[0, 1]		)

	# Execute the circuit on the qasm simulator
	A_     : Optional[Any]		      =						qiskit.execute(_lowerCamelCase     ,					_lowerCamelCase     ,					shots=1000		)

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


if __name__ == "__main__":
		_lowerCamelCase     :	Optional[int]         =				single_qubit_measure(2, 2)
		print(f'Total count for various states are: {counts}')













"""simple docstring"""





import json
from typing import Iterator, List, Union

from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing






class      a						(					__snake_case		):






    def __init__(       self     :							List[Any]       ,						__SCREAMING_SNAKE_CASE     :							str = "▁"       ,						__SCREAMING_SNAKE_CASE     :							bool = True       ,						__SCREAMING_SNAKE_CASE     :							Union[str, AddedToken] = "<unk>"       ,						__SCREAMING_SNAKE_CASE     :							Union[str, AddedToken] = "</s>"       ,						__SCREAMING_SNAKE_CASE     :							Union[str, AddedToken] = "<pad>"       ,						)     ->		Optional[int]:
      lowerCamelCase_         =						{
          'pad': {'id': 0, 'token': pad_token},
          'eos': {'id': 1, 'token': eos_token},
          'unk': {'id': 2, 'token': unk_token},
      }

      lowerCamelCase_         =						[None] * len(self.special_tokens					)
      for token_dict in self.special_tokens.values():
        lowerCamelCase_         =						token_dict['token']

      lowerCamelCase_         =						Tokenizer(Unigram()					)

      lowerCamelCase_         =						normalizers.Sequence(
          [
              normalizers.Nmt(),
              normalizers.NFKC(),
              normalizers.Replace(Regex(' {2,}'					)       ,						' '					),
              normalizers.Lowercase(),
          ]					)
      lowerCamelCase_         =						pre_tokenizers.Sequence(
          [
              pre_tokenizers.Metaspace(replacement=__SCREAMING_SNAKE_CASE       ,						add_prefix_space=__SCREAMING_SNAKE_CASE					),
              pre_tokenizers.Digits(individual_digits=__SCREAMING_SNAKE_CASE					),
              pre_tokenizers.Punctuation(),
          ]					)
      lowerCamelCase_         =						decoders.Metaspace(replacement=__SCREAMING_SNAKE_CASE       ,						add_prefix_space=__SCREAMING_SNAKE_CASE					)

      lowerCamelCase_         =						TemplateProcessing(
          single=F'''$A {self.special_tokens["eos"]["token"]}'''       ,						special_tokens=[(self.special_tokens['eos']['token'], self.special_tokens['eos']['id'])]       ,						)

      lowerCamelCase_         =						{
          'model': 'SentencePieceUnigram',
          'replacement': replacement,
          'add_prefix_space': add_prefix_space,
      }

      super().__init__(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)






    def    UpperCamelCase       (       self     :							Tuple       ,						__SCREAMING_SNAKE_CASE     :							Union[str, List[str]]       ,						__SCREAMING_SNAKE_CASE     :							int = 8000       ,						__SCREAMING_SNAKE_CASE     :							bool = True       ,						)     ->		Tuple:
      lowerCamelCase_         =						trainers.UnigramTrainer(
          vocab_size=__SCREAMING_SNAKE_CASE       ,						special_tokens=self.special_tokens_list       ,						show_progress=__SCREAMING_SNAKE_CASE       ,						)

      if isinstance(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					):
        lowerCamelCase_         =						[files]
      self._tokenizer.train(__SCREAMING_SNAKE_CASE       ,						trainer=__SCREAMING_SNAKE_CASE					)

      self.add_unk_id()






    def    UpperCamelCase       (       self     :							Tuple       ,						__SCREAMING_SNAKE_CASE     :							Union[Iterator[str], Iterator[Iterator[str]]]       ,						__SCREAMING_SNAKE_CASE     :							int = 8000       ,						__SCREAMING_SNAKE_CASE     :							bool = True       ,						)     ->		str:
      lowerCamelCase_         =						trainers.UnigramTrainer(
          vocab_size=__SCREAMING_SNAKE_CASE       ,						special_tokens=self.special_tokens_list       ,						show_progress=__SCREAMING_SNAKE_CASE       ,						)

      self._tokenizer.train_from_iterator(__SCREAMING_SNAKE_CASE       ,						trainer=__SCREAMING_SNAKE_CASE					)

      self.add_unk_id()






    def    UpperCamelCase       (       self     :							List[Any]					)     ->		Dict:
      lowerCamelCase_         =						json.loads(self._tokenizer.to_str()					)

      lowerCamelCase_         =						self.special_tokens['unk']['id']

      lowerCamelCase_         =						Tokenizer.from_str(json.dumps(__SCREAMING_SNAKE_CASE					)					)




