PassManager

append(passes, max_iteration=None, **flow_controller_conditions)

Append a Pass Set to the schedule of passes.

Parameters

• passes (Task | list(opens in a new tab)[Task]) – A set of passes (a pass set) to be added to schedule. A pass set is a list of passes that are controlled by the same flow controller. If a single pass is provided, the pass set will only have that pass a single element. It is also possible to append a BaseFlowController instance and the rest of the parameter will be ignored.

• max_iteration (int(opens in a new tab)) – max number of iterations of passes.

• flow_controller_conditions (Any) –

  Dictionary of control flow plugins. Following built-in controllers are available by default:

  • do_while: The passes repeat until the callable returns False. Corresponds to DoWhileController.
  • condition: The passes run only if the callable returns True. Corresponds to ConditionalController.

  In general, you have more control simply by creating the controller you want and passing it to append().

Raises

TranspilerError – if a pass in passes is not a proper pass.

draw(filename=None, style=None, raw=False)

Draw the pass manager.

This function needs pydot(opens in a new tab), which in turn needs Graphviz(opens in a new tab) to be installed.

Parameters

• filename (str(opens in a new tab)) – file path to save image to.
• style (dict(opens in a new tab)) – keys are the pass classes and the values are the colors to make them. An example can be seen in the DEFAULT_STYLE. An ordered dict can be used to ensure a priority coloring when pass falls into multiple categories. Any values not included in the provided dict will be filled in from the default dict.
• raw (bool(opens in a new tab)) – If True, save the raw Dot output instead of the image.

Returns

an in-memory representation of the pass manager, or None if no image was generated or Pillow(opens in a new tab) is not installed.

Return type

Optional[PassManager]

Raises

ImportError(opens in a new tab) – when nxpd or pydot not installed.

passes()

Return a list structure of the appended passes and its options.

Returns

A list of pass sets, as defined in append().

Return type

list(opens in a new tab)[dict(opens in a new tab)[str(opens in a new tab), qiskit.transpiler.basepasses.BasePass]]

remove(index)

Removes a particular pass in the scheduler.

Parameters

index (int(opens in a new tab)) – Pass index to remove, based on the position in passes().

Raises

PassManagerError – If the index is not found.

replace(index, passes, max_iteration=None, **flow_controller_conditions)

Replace a particular pass in the scheduler.

Parameters

• index (int(opens in a new tab)) – Pass index to replace, based on the position in passes().
• passes (Task | list(opens in a new tab)[Task]) – A pass set to be added to the pass manager schedule.
• max_iteration (int(opens in a new tab)) – max number of iterations of passes.
• flow_controller_conditions (Any) – Dictionary of control flow plugins. See qiskit.transpiler.PassManager.append() for details.

run(circuits, output_name=None, callback=None)

Run all the passes on the specified circuits.

Parameters

• circuits (_CircuitsT) – Circuit(s) to transform via all the registered passes.

• output_name (str(opens in a new tab) | None) – The output circuit name. If None, it will be set to the same as the input circuit name.

• callback (Callable) –

  A callback function that will be called after each pass execution. The function will be called with 5 keyword arguments:

  pass_ (Pass): the pass being run
  dag (DAGCircuit): the dag output of the pass
  time (float): the time to execute the pass
  property_set (PropertySet): the property set
  count (int): the index for the pass execution

  Note

  Beware that the keyword arguments here are different to those used by the generic BasePassManager. This pass manager will translate those arguments into the form described above.

  The exact arguments pass expose the internals of the pass manager and are subject to change as the pass manager internals change. If you intend to reuse a callback function over multiple releases be sure to check that the arguments being passed are the same.

  To use the callback feature you define a function that will take in kwargs dict and access the variables. For example:

  def callback_func(**kwargs):
      pass_ = kwargs['pass_']
      dag = kwargs['dag']
      time = kwargs['time']
      property_set = kwargs['property_set']
      count = kwargs['count']
      ...

Returns

The transformed circuit(s).

Return type

_CircuitsT

to_flow_controller()

Linearize this manager into a single FlowControllerLinear, so that it can be nested inside another pass manager.

Returns

A linearized pass manager.

Return type

RunningPassManager