text: # This code is part of Qiskit.
  #
  # (C) Copyright IBM 2017, 2019.
  #
  # This code is licensed under the Apache License, Version 2.0. You may
  # obtain a copy of this license in the LICENSE.txt file in the root directory
  # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
  #
  # Any modifications or derivative works of this code must retain this
  # copyright notice, and modified files need to carry a notice indicating
  # that they have been altered from the originals.
  
  """
  ======================================================
  Executing Experiments (:mod:`qiskit.execute_function`)
  ======================================================
  
  .. currentmodule:: qiskit.execute_function
  
  .. autofunction:: execute
  """
  import logging
  from time import time
  from qiskit.compiler import transpile, assemble, schedule
  from qiskit.providers import BaseBackend
  from qiskit.providers.backend import Backend
  from qiskit.qobj.utils import MeasLevel, MeasReturnType
  from qiskit.pulse import Schedule, ScheduleBlock
  from qiskit.exceptions import QiskitError
  
  logger = logging.getLogger(__name__)
  
  
  def _log_submission_time(start_time, end_time):
      log_msg = "Total Job Submission Time - %.5f (ms)" % ((end_time - start_time) * 1000)
      logger.info(log_msg)
  
  
  def execute(
      experiments,
      backend,
      basis_gates=None,
      coupling_map=None,  # circuit transpile options
      backend_properties=None,
      initial_layout=None,
      seed_transpiler=None,
      optimization_level=None,
      pass_manager=None,
      qobj_id=None,
      qobj_header=None,
      shots=None,  # common run options
      memory=False,
      max_credits=None,
      seed_simulator=None,
      default_qubit_los=None,
      default_meas_los=None,  # schedule run options
      qubit_lo_range=None,
      meas_lo_range=None,
      schedule_los=None,
      meas_level=None,
      meas_return=None,
      memory_slots=None,
      memory_slot_size=None,
      rep_time=None,
      rep_delay=None,
      parameter_binds=None,
      schedule_circuit=False,
      inst_map=None,
      meas_map=None,
      scheduling_method=None,
      init_qubits=None,
      **run_config,
  ):
      """Execute a list of :class:`qiskit.circuit.QuantumCircuit` or
      :class:`qiskit.pulse.Schedule` on a backend.
  
      The execution is asynchronous, and a handle to a job instance is returned.
  
      Args:
          experiments (QuantumCircuit or list[QuantumCircuit] or Schedule or list[Schedule]):
              Circuit(s) or pulse schedule(s) to execute
  
          backend (BaseBackend or Backend):
              Backend to execute circuits on.
              Transpiler options are automatically grabbed from
              backend.configuration() and backend.properties().
              If any other option is explicitly set (e.g. coupling_map), it
              will override the backend's.
  
          basis_gates (list[str]):
              List of basis gate names to unroll to.
              e.g: ``['u1', 'u2', 'u3', 'cx']``
              If ``None``, do not unroll.
  
          coupling_map (CouplingMap or list): Coupling map (perhaps custom) to
              target in mapping. Multiple formats are supported:
  
              #. CouplingMap instance
              #. list
                 Must be given as an adjacency matrix, where each entry
                 specifies all two-qubit interactions supported by backend
                 e.g:
                 ``[[0, 1], [0, 3], [1, 2], [1, 5], [2, 5], [4, 1], [5, 3]]``
  
          backend_properties (BackendProperties):
              Properties returned by a backend, including information on gate
              errors, readout errors, qubit coherence times, etc. Find a backend
              that provides this information with:
              ``backend.properties()``
  
          initial_layout (Layout or dict or list):
              Initial position of virtual qubits on physical qubits.
              If this layout makes the circuit compatible with the coupling_map
              constraints, it will be used.
              The final layout is not guaranteed to be the same, as the transpiler
              may permute qubits through swaps or other means.
  
              Multiple formats are supported:
  
              #. :class:`qiskit.transpiler.Layout` instance
              #. ``dict``:
                 virtual to physical::
  
                      {qr[0]: 0,
                       qr[1]: 3,
                       qr[2]: 5}
  
                 physical to virtual::
                      {0: qr[0],
                       3: qr[1],
                       5: qr[2]}
  
              #. ``list``
                 virtual to physical::
  
                      [0, 3, 5]  # virtual qubits are ordered (in addition to named)
  
                 physical to virtual::
  
                      [qr[0], None, None, qr[1], None, qr[2]]
  
          seed_transpiler (int): Sets random seed for the stochastic parts of the transpiler
  
          optimization_level (int): How much optimization to perform on the circuits.
              Higher levels generate more optimized circuits,
              at the expense of longer transpilation time.
              #. No optimization
              #. Light optimization
              #. Heavy optimization
              #. Highest optimization
              If None, level 1 will be chosen as default.
  
          pass_manager (PassManager): The pass manager to use during transpilation. If this
              arg is present, auto-selection of pass manager based on the transpile options
              will be turned off and this pass manager will be used directly.
  
          qobj_id (str): String identifier to annotate the Qobj
  
          qobj_header (QobjHeader or dict): User input that will be inserted in Qobj header,
              and will also be copied to the corresponding :class:`qiskit.result.Result`
              header. Headers do not affect the run.
  
          shots (int): Number of repetitions of each circuit, for sampling. Default: 1024
  
          memory (bool): If True, per-shot measurement bitstrings are returned as well
              (provided the backend supports it). For OpenPulse jobs, only
              measurement level 2 supports this option. Default: False
  
          max_credits (int): Maximum credits to spend on job. Default: 10
  
          seed_simulator (int): Random seed to control sampling, for when backend is a simulator
  
          default_qubit_los (Optional[List[float]]): List of job level qubit drive LO frequencies
              in Hz. Overridden by ``schedule_los`` if specified. Must have length ``n_qubits``.
  
          default_meas_los (Optional[List[float]]): List of job level measurement LO frequencies in
              Hz. Overridden by ``schedule_los`` if specified. Must have length ``n_qubits``.
  
          qubit_lo_range (Optional[List[List[float]]]): List of job level drive LO ranges each of form
              ``[range_min, range_max]`` in Hz. Used to validate ``qubit_lo_freq``. Must have length
              ``n_qubits``.
  
          meas_lo_range (Optional[List[List[float]]]): List of job level measurement LO ranges each of
              form ``[range_min, range_max]`` in Hz. Used to validate ``meas_lo_freq``. Must have
              length ``n_qubits``.
  
          schedule_los (list):
              Experiment level (ie circuit or schedule) LO frequency configurations for qubit drive
              and measurement channels. These values override the job level values from
              ``default_qubit_los`` and ``default_meas_los``. Frequencies are in Hz. Settable for qasm
              and pulse jobs.
  
              If a single LO config or dict is used, the values are set at job level. If a list is
              used, the list must be the size of the number of experiments in the job, except in the
              case of a single experiment. In this case, a frequency sweep will be assumed and one
              experiment will be created for every list entry.
  
              Not every channel is required to be specified. If not specified, the backend default
              value will be used.
  
          meas_level (int or MeasLevel): Set the appropriate level of the
              measurement output for pulse experiments.
  
          meas_return (str or MeasReturn): Level of measurement data for the
              backend to return For ``meas_level`` 0 and 1:
              ``"single"`` returns information from every shot.
              ``"avg"`` returns average measurement output (averaged over number
              of shots).
  
          memory_slots (int): Number of classical memory slots used in this job.
  
          memory_slot_size (int): Size of each memory slot if the output is Level 0.
  
          rep_time (int): Time per program execution in seconds. Must be from the list provided
              by the backend (``backend.configuration().rep_times``). Defaults to the first entry.
  
          rep_delay (float): Delay between programs in seconds. Only supported on certain
              backends (``backend.configuration().dynamic_reprate_enabled`` ). If supported,
              ``rep_delay`` will be used instead of ``rep_time`` and must be from the range supplied
              by the backend (``backend.configuration().rep_delay_range``). Default is given by
              ``backend.configuration().default_rep_delay``.
  
          parameter_binds (list[dict]): List of Parameter bindings over which the set of
              experiments will be executed. Each list element (bind) should be of the form
              ``{Parameter1: value1, Parameter2: value2, ...}``. All binds will be
              executed across all experiments, e.g. if parameter_binds is a
              length-n list, and there are m experiments, a total of :math:`m x n`
              experiments will be run (one for each experiment/bind pair).
  
          schedule_circuit (bool): If ``True``, ``experiments`` will be converted to
              :class:`qiskit.pulse.Schedule` objects prior to execution.
  
          inst_map (InstructionScheduleMap):
              Mapping of circuit operations to pulse schedules. If None, defaults to the
              ``instruction_schedule_map`` of ``backend``.
  
          meas_map (list(list(int))):
              List of sets of qubits that must be measured together. If None, defaults to
              the ``meas_map`` of ``backend``.
  
          scheduling_method (str or list(str)):
              Optionally specify a particular scheduling method.
  
          init_qubits (bool): Whether to reset the qubits to the ground state for each shot.
                              Default: ``True``.
  
          run_config (dict):
              Extra arguments used to configure the run (e.g. for Aer configurable backends).
              Refer to the backend documentation for details on these arguments.
              Note: for now, these keyword arguments will both be copied to the
              Qobj config, and passed to backend.run()
  
      Returns:
          BaseJob: returns job instance derived from BaseJob
  
      Raises:
          QiskitError: if the execution cannot be interpreted as either circuits or schedules
  
      Example:
          Construct a 5-qubit GHZ circuit and execute 4321 shots on a backend.
  
          .. jupyter-execute::
  
              from qiskit import QuantumCircuit, execute, BasicAer
  
              backend = BasicAer.get_backend('qasm_simulator')
  
              qc = QuantumCircuit(5, 5)
              qc.h(0)
              qc.cx(0, range(1, 5))
              qc.measure_all()
  
              job = execute(qc, backend, shots=4321)
      """
      if isinstance(experiments, (Schedule, ScheduleBlock)) or (
          isinstance(experiments, list) and isinstance(experiments[0], (Schedule, ScheduleBlock))
      ):
          # do not transpile a schedule circuit
          if schedule_circuit:
              raise QiskitError("Must supply QuantumCircuit to schedule circuit.")
      elif pass_manager is not None:
          # transpiling using pass_manager
          _check_conflicting_argument(
              optimization_level=optimization_level,
              basis_gates=basis_gates,
              coupling_map=coupling_map,
              seed_transpiler=seed_transpiler,
              backend_properties=backend_properties,
              initial_layout=initial_layout,
          )
          experiments = pass_manager.run(experiments)
      else:
          # transpiling the circuits using given transpile options
          experiments = transpile(
              experiments,
              basis_gates=basis_gates,
              coupling_map=coupling_map,
              backend_properties=backend_properties,
              initial_layout=initial_layout,
              seed_transpiler=seed_transpiler,
              optimization_level=optimization_level,
              backend=backend,
          )
  
      if schedule_circuit:
          experiments = schedule(
              circuits=experiments,
              backend=backend,
              inst_map=inst_map,
              meas_map=meas_map,
              method=scheduling_method,
          )
  
      if isinstance(backend, BaseBackend):
          # assembling the circuits into a qobj to be run on the backend
          if shots is None:
              shots = 1024
          if max_credits is None:
              max_credits = 10
          if meas_level is None:
              meas_level = MeasLevel.CLASSIFIED
          if meas_return is None:
              meas_return = MeasReturnType.AVERAGE
          if memory_slot_size is None:
              memory_slot_size = 100
  
          qobj = assemble(
              experiments,
              qobj_id=qobj_id,
              qobj_header=qobj_header,
              shots=shots,
              memory=memory,
              max_credits=max_credits,
              seed_simulator=seed_simulator,
              qubit_lo_freq=default_qubit_los,
              meas_lo_freq=default_meas_los,
              qubit_lo_range=qubit_lo_range,
              meas_lo_range=meas_lo_range,
              schedule_los=schedule_los,
              meas_level=meas_level,
              meas_return=meas_return,
              memory_slots=memory_slots,
              memory_slot_size=memory_slot_size,
              rep_time=rep_time,
              rep_delay=rep_delay,
              parameter_binds=parameter_binds,
              backend=backend,
              init_qubits=init_qubits,
              **run_config,
          )
  
          # executing the circuits on the backend and returning the job
          start_time = time()
          job = backend.run(qobj, **run_config)
          end_time = time()
          _log_submission_time(start_time, end_time)
      elif isinstance(backend, Backend):
          start_time = time()
          run_kwargs = {
              "shots": shots,
              "memory": memory,
              "seed_simulator": seed_simulator,
              "qubit_lo_freq": default_qubit_los,
              "meas_lo_freq": default_meas_los,
              "qubit_lo_range": qubit_lo_range,
              "meas_lo_range": meas_lo_range,
              "schedule_los": schedule_los,
              "meas_level": meas_level,
              "meas_return": meas_return,
              "memory_slots": memory_slots,
              "memory_slot_size": memory_slot_size,
              "rep_time": rep_time,
              "rep_delay": rep_delay,
              "init_qubits": init_qubits,
          }
          for key in list(run_kwargs.keys()):
              if not hasattr(backend.options, key):
                  if run_kwargs[key] is not None:
                      logger.info(
                          "%s backend doesn't support option %s so not "
                          "passing that kwarg to run()",
                          backend.name,
                          key,
                      )
                  del run_kwargs[key]
              elif key == "shots" and run_kwargs[key] is None:
                  run_kwargs[key] = 1024
              elif key == "max_credits" and run_kwargs[key] is None:
                  run_kwargs[key] = 10
              elif key == "meas_level" and run_kwargs[key] is None:
                  run_kwargs[key] = MeasLevel.CLASSIFIED
              elif key == "meas_return" and run_kwargs[key] is None:
                  run_kwargs[key] = MeasReturnType.AVERAGE
              elif key == "memory_slot_size" and run_kwargs[key] is None:
                  run_kwargs[key] = 100
  
          run_kwargs["parameter_binds"] = parameter_binds
          run_kwargs.update(run_config)
          job = backend.run(experiments, **run_kwargs)
          end_time = time()
          _log_submission_time(start_time, end_time)
      else:
          raise QiskitError("Invalid backend type %s" % type(backend))
      return job
  
  
  def _check_conflicting_argument(**kargs):
      conflicting_args = [arg for arg, value in kargs.items() if value]
      if conflicting_args:
          raise QiskitError(
              "The parameters pass_manager conflicts with the following "
              "parameter(s): {}.".format(", ".join(conflicting_args))
          )
  