



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)}""")









"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase					=     {
    """configuration_led""": ["""LED_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LEDConfig"""],
    """tokenization_led""": ["""LEDTokenizer"""],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase					=     ["""LEDTokenizerFast"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase					=     [
      """LED_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """LEDForConditionalGeneration""",
      """LEDForQuestionAnswering""",
      """LEDForSequenceClassification""",
      """LEDModel""",
      """LEDPreTrainedModel""",
  ]


try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase					=     ["""TFLEDForConditionalGeneration""", """TFLEDModel""", """TFLEDPreTrainedModel"""]


if TYPE_CHECKING:
  from .configuration_led import LED_PRETRAINED_CONFIG_ARCHIVE_MAP, LEDConfig
  from .tokenization_led import LEDTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_led_fast import LEDTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_led import (
        LED_PRETRAINED_MODEL_ARCHIVE_LIST,
        LEDForConditionalGeneration,
        LEDForQuestionAnswering,
        LEDForSequenceClassification,
        LEDModel,
        LEDPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_led import TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel

else:
  import sys

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






