




"""simple docstring"""
import numpy as np
import qiskit






def 				__lowerCAmelCase					(					__lowerCAmelCase			:		List[str]  ,	__lowerCAmelCase			:		List[Any]						)    ->       Optional[int]:
 _UpperCamelCase      :	Union[str, Any]					      =  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      :	Optional[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(__lowerCamelCase  ,	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(__lowerCamelCase						):
   if bit == "1":
    oracle_qc.x(__lowerCamelCase						)
        # Do the controlled-NOT gates for each qubit, using the output qubit
        # as the target:
  for index in range(__lowerCamelCase						):
   oracle_qc.cx(__lowerCamelCase  ,	__lowerCamelCase						)
  # Next, place the final X-gates
  for index, bit in enumerate(__lowerCamelCase						):
   if bit == "1":
    oracle_qc.x(__lowerCamelCase						)

    # 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      :	str					      =  np.random.randint(2						)
  if output == 1:
   oracle_qc.x(__lowerCamelCase						)

 _UpperCamelCase      :	Optional[int]					      =  oracle_qc.to_gate()
 _UpperCamelCase      :	Tuple					      =  "Oracle"  # To show when we display the circuit
 return oracle_gate






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

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

 return dj_circuit






def 				__lowerCAmelCase					(					__lowerCAmelCase			:		Optional[int]  ,	__lowerCAmelCase			:		Optional[int]						)    ->       Tuple:
 _UpperCamelCase      :	Optional[int]					      =  qiskit.Aer.get_backend("aer_simulator"						)

 _UpperCamelCase      :	List[Any]					      =  dj_oracle(__lowerCamelCase  ,	__lowerCamelCase						)
 _UpperCamelCase      :	List[str]					      =  dj_algorithm(__lowerCamelCase  ,	__lowerCamelCase						)

 # Execute the circuit on the simulator
 _UpperCamelCase      :	Tuple					      =  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__":
    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


__UpperCAmelCase   						=     {
    "configuration_donut_swin": ["DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "DonutSwinConfig"],
    "processing_donut": ["DonutProcessor"],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __UpperCAmelCase   						=     [
       "DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
       "DonutSwinModel",
       "DonutSwinPreTrainedModel",
   ]

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __UpperCAmelCase   						=     ["DonutFeatureExtractor"]
   __UpperCAmelCase   						=     ["DonutImageProcessor"]


if TYPE_CHECKING:
   from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
   from .processing_donut import DonutProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_donut_swin import (
          DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
          DonutSwinModel,
          DonutSwinPreTrainedModel,
      )

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_donut import DonutFeatureExtractor
      from .image_processing_donut import DonutImageProcessor

else:
   import sys

   __UpperCAmelCase   						=     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


