code: 
  '''simple docstring'''
  
  import doctest
  
  import projectq
  from projectq.ops import H, Measure
  
  
  
  
  
  
  
  def 						snake_case__	(      UpperCamelCase	) ->      int:
  		_UpperCamelCase       : Optional[int]    =      quantum_engine.allocate_qubit()
  		H | qubit
  		Measure | qubit
  		return int(UpperCamelCase	)
  
  
  if __name__ == "__main__":
  	doctest.testmod()
  
  	# initialises a new quantum backend
  	_UpperCAmelCase   :      Optional[Any] 						=  projectq.MainEngine()
  
  	# Generate a list of 10 random numbers
  	_UpperCAmelCase   :      int 						=  [get_random_number(quantum_engine) for _ in range(10)]
  
  	# Flushes the quantum engine from memory
  	quantum_engine.flush()
  
  	print("""Random numbers""", random_numbers_list)
  
  
  
  
  
  
style_context: 
  '''simple docstring'''
  
  _UpperCAmelCase   :      Optional[int] 						=  """
  # Transformers installation
  ! pip install transformers datasets evaluate
  # To install from source instead of the last release, comment the command above and uncomment the following one.
  # ! pip install git+https://github.com/huggingface/transformers.git
  """
  
  _UpperCAmelCase   :      Union[str, Any] 						=  [{"""type""": """code""", """content""": INSTALL_CONTENT}]
  _UpperCAmelCase   :      Union[str, Any] 						=  {
      """{processor_class}""": """FakeProcessorClass""",
      """{model_class}""": """FakeModelClass""",
      """{object_class}""": """FakeObjectClass""",
  }
  
  
  
  
  
  