



import numpy as np
import qiskit


def 						UpperCAmelCase__   (   UpperCAmelCase__			:str			,       UpperCAmelCase__			:int       ):






 '''simple docstring'''

 a							=		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:
  a							=		np.random.randint(1			,       2**num_qubits       )
  # Next, format 'b' as a binary string of length 'n', padded with zeros:
  a							=		format(UpperCAmelCase__			,       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(UpperCAmelCase__       ):
   if bit == "1":
    oracle_qc.x(UpperCAmelCase__       )
        # Do the controlled-NOT gates for each qubit, using the output qubit
        # as the target:
  for index in range(UpperCAmelCase__       ):
   oracle_qc.cx(UpperCAmelCase__			,       UpperCAmelCase__       )
  # Next, place the final X-gates
  for index, bit in enumerate(UpperCAmelCase__       ):
   if bit == "1":
    oracle_qc.x(UpperCAmelCase__       )

    # 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)
  a							=		np.random.randint(2       )
  if output == 1:
   oracle_qc.x(UpperCAmelCase__       )

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


def 						UpperCAmelCase__   (   UpperCAmelCase__			:qiskit.QuantumCircuit			,       UpperCAmelCase__			:int       ):






 '''simple docstring'''

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

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

 return dj_circuit


def 						UpperCAmelCase__   (   UpperCAmelCase__			:str			,       UpperCAmelCase__			:int       ):






 '''simple docstring'''

 a							=		qiskit.Aer.get_backend("aer_simulator"       )

 a							=		dj_oracle(UpperCAmelCase__			,       UpperCAmelCase__       )
 a							=		dj_algorithm(UpperCAmelCase__			,       UpperCAmelCase__       )

 # Execute the circuit on the simulator
 a							=		qiskit.execute(UpperCAmelCase__			,       UpperCAmelCase__			,       shots=10_00       )

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


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






from typing import TYPE_CHECKING

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


A_		:  Any										=  {
    '''configuration_videomae''': ['''VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VideoMAEConfig'''],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A_		:  List[Any]										=  [
         '''VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''VideoMAEForPreTraining''',
         '''VideoMAEModel''',
         '''VideoMAEPreTrainedModel''',
         '''VideoMAEForVideoClassification''',
     ]

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A_		:  str										=  ['''VideoMAEFeatureExtractor''']
     A_		:  Union[str, Any]										=  ['''VideoMAEImageProcessor''']

if TYPE_CHECKING:
     from .configuration_videomae import VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP, VideoMAEConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_videomae import (
              VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST,
              VideoMAEForPreTraining,
              VideoMAEForVideoClassification,
              VideoMAEModel,
              VideoMAEPreTrainedModel,
          )

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_videomae import VideoMAEFeatureExtractor
          from .image_processing_videomae import VideoMAEImageProcessor

else:
     import sys

     A_		:  Dict										=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

