

"""simple docstring"""






import qiskit





def 	lowercase      (   __UpperCamelCase      ,   __UpperCamelCase						) ->      qiskit.result.counts.Counts:
 __magic_name__     =      qiskit.Aer.get_backend('''aer_simulator'''						)

 # Create a Quantum Circuit acting on the q register
 __magic_name__     =      qiskit.QuantumCircuit(__UpperCamelCase      ,   __UpperCamelCase						)

 # Apply X (NOT) Gate to Qubits 0 & 1
 circuit.x(0						)
 circuit.x(1						)

 # Map the quantum measurement to the classical bits
 circuit.measure([0, 1]      ,   [0, 1]						)

 # Execute the circuit on the qasm simulator
 __magic_name__     =      qiskit.execute(__UpperCamelCase      ,   __UpperCamelCase      ,   shots=1000						)

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


if __name__ == "__main__":
 __lowerCamelCase										=		single_qubit_measure(2, 2)
 print(f"""Total count for various states are: {counts}""")




"""simple docstring"""






from typing import TYPE_CHECKING

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


__lowerCamelCase										=		{
    "configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", "M2M100OnnxConfig"],
    "tokenization_m2m_100": ["M2M100Tokenizer"],
}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCamelCase										=		[
     "M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST",
     "M2M100ForConditionalGeneration",
     "M2M100Model",
     "M2M100PreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_mam_aaa import M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP, MaMaaaConfig, MaMaaaOnnxConfig
 from .tokenization_mam_aaa import MaMaaaTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_mam_aaa import (
      M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST,
      MaMaaaForConditionalGeneration,
      MaMaaaModel,
      MaMaaaPreTrainedModel,
  )


else:
 import sys

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

