"""simple docstring"""






import numpy as np
import qiskit



def     a_		(   lowerCamelCase   ,     lowerCamelCase			):
				UpperCAmelCase__			 =				qiskit.QuantumCircuit(num_qubits + 1			)

				# First, let's deal with the case in which oracle is balanced
				if case == "balanced":
								# First generate a random number that tells us which CNOTs to
								# wrap in X-gates:
								UpperCAmelCase__			 =				np.random.randint(1   ,     2**num_qubits			)
								# Next, format 'b' as a binary string of length 'n', padded with zeros:
								UpperCAmelCase__			 =				format(lowercase__   ,     f'''0{num_qubits}b'''			)
								# Next, we place the first X-gates. Each digit in our binary string
								# corresponds to a qubit, if the digit is 0, we do nothing, if it's 1
								# we apply an X-gate to that qubit:
								for index, bit in enumerate(lowercase__			):
												if bit == "1":
																oracle_qc.x(lowercase__			)
        # Do the controlled-NOT gates for each qubit, using the output qubit
        # as the target:
								for index in range(lowercase__			):
												oracle_qc.cx(lowercase__   ,     lowercase__			)
								# Next, place the final X-gates
								for index, bit in enumerate(lowercase__			):
												if bit == "1":
																oracle_qc.x(lowercase__			)

    # Case in which oracle is constant
				if case == "constant":
								# First decide what the fixed output of the oracle will be
								# (either always 0 or always 1)
								UpperCAmelCase__			 =				np.random.randint(2			)
								if output == 1:
												oracle_qc.x(lowercase__			)

				UpperCAmelCase__			 =				oracle_qc.to_gate()
				UpperCAmelCase__			 =				'Oracle'  # To show when we display the circuit
				return oracle_gate



def     a_		(   lowerCamelCase   ,     lowerCamelCase			):
				UpperCAmelCase__			 =				qiskit.QuantumCircuit(num_qubits + 1   ,     lowercase__			)
				# Set up the output qubit:
				dj_circuit.x(lowercase__			)
				dj_circuit.h(lowercase__			)
				# And set up the input register:
				for qubit in range(lowercase__			):
								dj_circuit.h(lowercase__			)
				# Let's append the oracle gate to our circuit:
				dj_circuit.append(lowercase__   ,     range(num_qubits + 1			)			)
				# Finally, perform the H-gates again and measure:
				for qubit in range(lowercase__			):
								dj_circuit.h(lowercase__			)

				for i in range(lowercase__			):
								dj_circuit.measure(lowercase__   ,     lowercase__			)

				return dj_circuit



def     a_		(   lowerCamelCase   ,     lowerCamelCase			):
				UpperCAmelCase__			 =				qiskit.Aer.get_backend('aer_simulator'			)

				UpperCAmelCase__			 =				dj_oracle(lowercase__   ,     lowercase__			)
				UpperCAmelCase__			 =				dj_algorithm(lowercase__   ,     lowercase__			)

				# Execute the circuit on the simulator
				UpperCAmelCase__			 =				qiskit.execute(lowercase__   ,     lowercase__   ,     shots=1_0_0_0			)

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


if __name__ == "__main__":
						print(F"""Deutsch Jozsa - Constant Oracle: {deutsch_jozsa('constant', 3)}""")
						print(F"""Deutsch Jozsa - Balanced Oracle: {deutsch_jozsa('balanced', 3)}""")






"""simple docstring"""




import inspect
import json
import os
import tempfile
import unittest

from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES

from ...test_tokenization_common import TokenizerTesterMixin





class      __UpperCamelCase					(  _A	,						unittest.TestCase		):
		SCREAMING_SNAKE_CASE														=       SpeechaTextaTokenizer
		SCREAMING_SNAKE_CASE														=       False


		def    SCREAMING_SNAKE_CASE__  (self					:						Tuple):
							super().setUp()

							A     =   "<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab".split(" ")
							A     =   ["he re</w> 123", "here a 1456"]
							A     =   dict(zip(__SCREAMING_SNAKE_CASE	,	range(len(__SCREAMING_SNAKE_CASE))))

							A     =   {"pad_token": "<pad>", "unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>"}

							A     =   tempfile.mkdtemp()
							A     =   os.path.join(self.tmpdirname	,	VOCAB_FILES_NAMES["vocab_file"])
							A     =   os.path.join(self.tmpdirname	,	VOCAB_FILES_NAMES["merges_file"])

							with open(self.vocab_file	,	"w"	,	encoding="utf-8") as fp:
												fp.write(json.dumps(__SCREAMING_SNAKE_CASE) + "\n")

							with open(self.merges_file	,	"w") as fp:
												fp.write("\n".join(__SCREAMING_SNAKE_CASE))


		def    SCREAMING_SNAKE_CASE__  (self					:						Union[str, Any]):
							A     =   list(self.get_tokenizer().get_vocab().keys())

							self.assertEqual(vocab_keys[0]	,	"<s>")
							self.assertEqual(vocab_keys[1]	,	"<pad>")
							self.assertEqual(vocab_keys[-1]	,	"vocab")
							self.assertEqual(len(__SCREAMING_SNAKE_CASE)	,	1_4)


		def    SCREAMING_SNAKE_CASE__  (self					:						Any):
							self.assertEqual(self.get_tokenizer().vocab_size	,	1_4)


		def    SCREAMING_SNAKE_CASE__  (self					:						Union[str, Any]):
							A     =   SpeechaTextaTokenizer.from_pretrained(self.tmpdirname)

							# make sure @@ is correctly concatenated
							A     =   [4, 6, 8, 7, 1_0]  # ["here@@", "couple", "words", "of@@", "the"]
							A     =   tokenizer.decode(__SCREAMING_SNAKE_CASE)

							self.assertTrue(output_string == "herecouple words ofthe")


		def    SCREAMING_SNAKE_CASE__  (self					:						str):
							A     =   SpeechaTextaTokenizer.from_pretrained(self.tmpdirname)

							with tempfile.TemporaryDirectory() as tmp_dirname:
												tokenizer.save_pretrained(__SCREAMING_SNAKE_CASE)
												os.remove(os.path.join(__SCREAMING_SNAKE_CASE	,	"merges.txt"))

												# load tokenizer without merges file should not throw an error
												A     =   SpeechaTextaTokenizer.from_pretrained(__SCREAMING_SNAKE_CASE)

							with tempfile.TemporaryDirectory() as tmp_dirname:
												# save tokenizer and load again
												tokenizer.save_pretrained(__SCREAMING_SNAKE_CASE)
												A     =   SpeechaTextaTokenizer.from_pretrained(__SCREAMING_SNAKE_CASE)

							self.assertIsNotNone(__SCREAMING_SNAKE_CASE)


		def    SCREAMING_SNAKE_CASE__  (self					:						Tuple):
							if not self.test_slow_tokenizer:
												return

							A     =   inspect.signature(self.tokenizer_class.__init__)
							A     =   self.get_tokenizer()

							for parameter_name, parameter in signature.parameters.items():
												if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
																	self.assertIn(__SCREAMING_SNAKE_CASE	,	tokenizer.init_kwargs)





