





'''simple docstring'''







import numpy as np
import qiskit





def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      str,      SCREAMING_SNAKE_CASE__   :      int )			->						qiskit.QuantumCircuit:
						UpperCAmelCase_      :   Optional[int]      =	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_      :   Any      =	np.random.randint(1,      2**num_qubits )
												# Next, format 'b' as a binary string of length 'n', padded with zeros:
												UpperCAmelCase_      :   Optional[int]      =	format(SCREAMING_SNAKE_CASE__,      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(SCREAMING_SNAKE_CASE__ ):
																		if bit == "1":
																								oracle_qc.x(SCREAMING_SNAKE_CASE__ )
        # Do the controlled-NOT gates for each qubit, using the output qubit
        # as the target:
												for index in range(SCREAMING_SNAKE_CASE__ ):
																		oracle_qc.cx(SCREAMING_SNAKE_CASE__,      SCREAMING_SNAKE_CASE__ )
												# Next, place the final X-gates
												for index, bit in enumerate(SCREAMING_SNAKE_CASE__ ):
																		if bit == "1":
																								oracle_qc.x(SCREAMING_SNAKE_CASE__ )

    # 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_      :   int      =	np.random.randint(2 )
												if output == 1:
																		oracle_qc.x(SCREAMING_SNAKE_CASE__ )

						UpperCAmelCase_      :   Union[str, Any]      =	oracle_qc.to_gate()
						UpperCAmelCase_      :   List[Any]      =	'''Oracle'''  # To show when we display the circuit
						return oracle_gate





def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      qiskit.QuantumCircuit,      SCREAMING_SNAKE_CASE__   :      int )			->						qiskit.QuantumCircuit:
						UpperCAmelCase_      :   List[str]      =	qiskit.QuantumCircuit(num_qubits + 1,      SCREAMING_SNAKE_CASE__ )
						# Set up the output qubit:
						dj_circuit.x(SCREAMING_SNAKE_CASE__ )
						dj_circuit.h(SCREAMING_SNAKE_CASE__ )
						# And set up the input register:
						for qubit in range(SCREAMING_SNAKE_CASE__ ):
												dj_circuit.h(SCREAMING_SNAKE_CASE__ )
						# Let's append the oracle gate to our circuit:
						dj_circuit.append(SCREAMING_SNAKE_CASE__,      range(num_qubits + 1 ) )
						# Finally, perform the H-gates again and measure:
						for qubit in range(SCREAMING_SNAKE_CASE__ ):
												dj_circuit.h(SCREAMING_SNAKE_CASE__ )

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

						return dj_circuit





def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      str,      SCREAMING_SNAKE_CASE__   :      int )			->						qiskit.result.counts.Counts:
						UpperCAmelCase_      :   Dict      =	qiskit.Aer.get_backend('''aer_simulator''' )

						UpperCAmelCase_      :   Dict      =	dj_oracle(SCREAMING_SNAKE_CASE__,      SCREAMING_SNAKE_CASE__ )
						UpperCAmelCase_      :   Optional[Any]      =	dj_algorithm(SCREAMING_SNAKE_CASE__,      SCREAMING_SNAKE_CASE__ )

						# Execute the circuit on the simulator
						UpperCAmelCase_      :   Tuple      =	qiskit.execute(SCREAMING_SNAKE_CASE__,      SCREAMING_SNAKE_CASE__,      shots=1000 )

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


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'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


snake_case_  :							Any            =	{
    "configuration_flava": [
        "FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "FlavaConfig",
        "FlavaImageCodebookConfig",
        "FlavaImageConfig",
        "FlavaMultimodalConfig",
        "FlavaTextConfig",
    ],
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_  :							List[str]            =	["FlavaFeatureExtractor"]
					snake_case_  :							int            =	["FlavaImageProcessor"]
					snake_case_  :							Tuple            =	["FlavaProcessor"]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_  :							Optional[int]            =	[
					    "FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "FlavaForPreTraining",
					    "FlavaImageCodebook",
					    "FlavaImageModel",
					    "FlavaModel",
					    "FlavaMultimodalModel",
					    "FlavaPreTrainedModel",
					    "FlavaTextModel",
					]

if TYPE_CHECKING:
					from .configuration_flava import (
					    FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    FlavaConfig,
					    FlavaImageCodebookConfig,
					    FlavaImageConfig,
					    FlavaMultimodalConfig,
					    FlavaTextConfig,
					)

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_flava import FlavaFeatureExtractor
										from .image_processing_flava import FlavaImageProcessor
										from .processing_flava import FlavaProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flava import (
										    FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST,
										    FlavaForPreTraining,
										    FlavaImageCodebook,
										    FlavaImageModel,
										    FlavaModel,
										    FlavaMultimodalModel,
										    FlavaPreTrainedModel,
										    FlavaTextModel,
										)

else:
					import sys

					snake_case_  :							Any            =	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





