




'''simple docstring'''

import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin



class 		SCREAMING_SNAKE_CASE__  (			_UpperCamelCase				,     unittest.TestCase	):
			__SCREAMING_SNAKE_CASE    =			XLMTokenizer
			__SCREAMING_SNAKE_CASE    =			False





			def 							A (      self						:    str							):



						"""simple docstring"""




						super().setUp()

						# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
						__snake_case			=		[
						    "l",
						    "o",
						    "w",
						    "e",
						    "r",
						    "s",
						    "t",
						    "i",
						    "d",
						    "n",
						    "w</w>",
						    "r</w>",
						    "t</w>",
						    "lo",
						    "low",
						    "er</w>",
						    "low</w>",
						    "lowest</w>",
						    "newer</w>",
						    "wider</w>",
						    "<unk>",
						]
						__snake_case			=		dict(zip(a_      ,		range(len(a_							)							)							)							)
						__snake_case			=		["l o 123", "lo w 1456", "e r</w> 1789", ""]

						__snake_case			=		os.path.join(self.tmpdirname      ,		VOCAB_FILES_NAMES["vocab_file"]							)
						__snake_case			=		os.path.join(self.tmpdirname      ,		VOCAB_FILES_NAMES["merges_file"]							)
						with open(self.vocab_file      ,		"w"							) as fp:
									fp.write(json.dumps(a_							)							)
						with open(self.merges_file      ,		"w"							) as fp:
									fp.write("\n".join(a_							)							)





			def 							A (      self						:    Union[str, Any]      ,		a_						:    Optional[int]							):



						"""simple docstring"""




						__snake_case			=		"lower newer"
						__snake_case			=		"lower newer"
						return input_text, output_text





			def 							A (      self						:    Dict							):



						"""simple docstring"""




						__snake_case			=		XLMTokenizer(self.vocab_file      ,		self.merges_file							)

						__snake_case			=		"lower"
						__snake_case			=		["low", "er</w>"]
						__snake_case			=		tokenizer.tokenize(a_							)
						self.assertListEqual(a_      ,		a_							)

						__snake_case			=		tokens + ["<unk>"]
						__snake_case			=		[14, 15, 20]
						self.assertListEqual(tokenizer.convert_tokens_to_ids(a_							)      ,		a_							)






			@slow
			def 							A (      self						:    List[str]							):



						"""simple docstring"""




						__snake_case			=		XLMTokenizer.from_pretrained("xlm-mlm-en-2048"							)

						__snake_case			=		tokenizer.encode("sequence builders"      ,		add_special_tokens=a_							)
						__snake_case			=		tokenizer.encode("multi-sequence build"      ,		add_special_tokens=a_							)

						__snake_case			=		tokenizer.build_inputs_with_special_tokens(a_							)
						__snake_case			=		tokenizer.build_inputs_with_special_tokens(a_      ,		a_							)

						assert encoded_sentence == [0] + text + [1]
						assert encoded_pair == [0] + text + [1] + text_a + [1]










'''simple docstring'''





import qiskit





def   a_   (		_UpperCAmelCase    :      int = 2				)    ->  qiskit.result.counts.Counts:
      __snake_case :   Union[str, Any]													=    qubits

      # Using Aer's simulator
      __snake_case :   List[Any]													=    qiskit.Aer.get_backend('aer_simulator'				)

      # Creating a Quantum Circuit acting on the q register
      __snake_case :   Dict													=    qiskit.QuantumCircuit(_UpperCAmelCase ,_UpperCAmelCase				)

      # Adding a H gate on qubit 0 (now q0 in superposition)
      circuit.h(0				)

      for i in range(1 ,_UpperCAmelCase				):
            # Adding CX (CNOT) gate
            circuit.cx(i - 1 ,_UpperCAmelCase				)

      # Mapping the quantum measurement to the classical bits
      circuit.measure(list(range(_UpperCAmelCase				)				) ,list(range(_UpperCAmelCase				)				)				)

      # Now measuring any one qubit would affect other qubits to collapse
      # their super position and have same state as the measured one.

      # Executing the circuit on the simulator
      __snake_case :   Optional[Any]													=    qiskit.execute(_UpperCAmelCase ,_UpperCAmelCase ,shots=10_00				)

      return job.result().get_counts(_UpperCAmelCase				)


if __name__ == "__main__":
    print(F"""Total count for various states are: {quantum_entanglement(3)}""")



