PassManager
class qiskit.transpiler.PassManager(passes=None, max_iteration=1000)
Bases: object
Manager for a set of Passes and their scheduling during transpilation.
Initialize an empty PassManager object (with no passes scheduled).
Parameters
- passes (BasePass | list[BasePass] | None) – A pass set (as defined in
qiskit.transpiler.PassManager.append()
) to be added to the pass manager schedule. - max_iteration (int) – The maximum number of iterations the schedule will be looped if the condition is not met.
Methods
append
append(passes, max_iteration=None, **flow_controller_conditions)
Append a Pass Set to the schedule of passes.
Parameters
- passes (BasePass | Sequence[BasePass | FlowController]) – 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
FlowController
instance and the rest of the parameter will be ignored. - max_iteration (int) – max number of iterations of passes.
- flow_controller_conditions (Any) – control flow plugins.
Raises
TranspilerError – if a pass in passes is not a proper pass.
RunningPassManager.add_flow_controller()
for more information about the control flow plugins.
draw
draw(filename=None, style=None, raw=False)
Draw the pass manager.
This function needs pydot, which in turn needs Graphviz to be installed.
Parameters
- filename (str) – file path to save image to.
- style (dict) – 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) – 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 is not installed.
Return type
Optional[PassManager]
Raises
ImportError – when nxpd or pydot not installed.
passes
passes()
Return a list structure of the appended passes and its options.
Returns
A list of pass sets, as defined in append()
.
Return type
remove
remove(index)
Removes a particular pass in the scheduler.
Parameters
index (int) – Pass index to replace, based on the position in passes().
Raises
TranspilerError – if the index is not found.
replace
replace(index, passes, max_iteration=None, **flow_controller_conditions)
Replace a particular pass in the scheduler.
Parameters
- index (int) – Pass index to replace, based on the position in passes().
- passes (BasePass | list[BasePass]) – A pass set (as defined in
qiskit.transpiler.PassManager.append()
) to be added to the pass manager schedule. - max_iteration (int) – max number of iterations of passes.
- flow_controller_conditions (Any) – control flow plugins.
Raises
TranspilerError – if a pass in passes is not a proper pass or index not found.
RunningPassManager.add_flow_controller()
for more information about the control flow plugins.
run
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 | None) – The output circuit name. If
None
, it will be set to the same as the input circuit name. -
callback (Callable | None) –
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
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
to_flow_controller()
Linearize this manager into a single FlowController
, so that it can be nested inside another PassManager
.
Return type