Synthesis Plugins
qiskit.transpiler.passes.synthesis.plugin
This module defines the plugin interfaces for the synthesis transpiler passes in Qiskit. These provide a hook point for external python packages to implement their own synthesis techniques and have them seamlessly exposed as opt-in options to users when they run transpile()
.
The plugin interfaces are built using setuptools entry points which enable packages external to qiskit to advertise they include a synthesis plugin.
See qiskit.transpiler.preset_passmanagers.plugin
for details on how to write plugins for transpiler stages.
Writing Plugins
Unitary Synthesis Plugins
To write a unitary synthesis plugin there are 2 main steps. The first step is to create a subclass of the abstract plugin class: UnitarySynthesisPlugin
. The plugin class defines the interface and contract for unitary synthesis plugins. The primary method is run()
which takes in a single positional argument, a unitary matrix as a numpy array, and is expected to return a DAGCircuit
object representing the synthesized circuit from that unitary matrix. Then to inform the Qiskit transpiler about what information is necessary for the pass there are several required property methods that need to be implemented such as supports_basis_gates
and supports_coupling_map
depending on whether the plugin supports and/or requires that input to perform synthesis. For the full details refer to the UnitarySynthesisPlugin
documentation for all the required fields. An example plugin class would look something like:
from qiskit.transpiler.passes.synthesis import plugin
from qiskit_plugin_pkg.synthesis import generate_dag_circuit_from_matrix
class SpecialUnitarySynthesis(plugin.UnitarySynthesisPlugin):
@property
def supports_basis_gates(self):
return True
@property
def supports_coupling_map(self):
return False
@property
def supports_natural_direction(self):
return False
@property
def supports_pulse_optimize(self):
return False
@property
def supports_gate_lengths(self):
return False
@property
def supports_gate_errors(self):
return False
@property
def min_qubits(self):
return None
@property
def max_qubits(self):
return None
@property
def supported_bases(self):
return None
def run(self, unitary, **options):
basis_gates = options['basis_gates']
dag_circuit = generate_dag_circuit_from_matrix(unitary, basis_gates)
return dag_circuit
If for some reason the available inputs to the run()
method are insufficient please open an issue and we can discuss expanding the plugin interface with new opt-in inputs that can be added in a backwards compatible manner for future releases. Do note though that this plugin interface is considered stable and guaranteed to not change in a breaking manner. If changes are needed (for example to expand the available optional input options) it will be done in a way that will not require changes from existing plugins.
All methods prefixed with supports_
are reserved on a UnitarySynthesisPlugin
derived class for part of the interface. You should not define any custom supports_*
methods on a subclass that are not defined in the abstract class.
The second step is to expose the UnitarySynthesisPlugin
as a setuptools entry point in the package metadata. This is done by simply adding an entry_points
entry to the setuptools.setup
call in the setup.py
for the plugin package with the necessary entry points under the qiskit.unitary_synthesis
namespace. For example:
entry_points = {
'qiskit.unitary_synthesis': [
'special = qiskit_plugin_pkg.module.plugin:SpecialUnitarySynthesis',
]
},
(note that the entry point name = path
is a single string not a Python expression). There isn’t a limit to the number of plugins a single package can include as long as each plugin has a unique name. So a single package can expose multiple plugins if necessary. The name default
is used by Qiskit itself and can’t be used in a plugin.
Unitary Synthesis Plugin Configuration
For some unitary synthesis plugins that expose multiple options and tunables the plugin interface has an option for users to provide a free form configuration dictionary. This will be passed through to the run()
method as the config
kwarg. If your plugin has these configuration options you should clearly document how a user should specify these configuration options and how they’re used as it’s a free form field.
High-Level Synthesis Plugins
Writing a high-level synthesis plugin is conceptually similar to writing a unitary synthesis plugin. The first step is to create a subclass of the abstract plugin class: HighLevelSynthesisPlugin
, which defines the interface and contract for high-level synthesis plugins. The primary method is run()
. It takes in a single positional argument, a “higher-level-object” to be synthesized, which is any object of type Operation
(including, for example, LinearFunction
or Clifford
). The method run()
is expected to return a QuantumCircuit
object representing the synthesized circuit from that higher-level-object. It is also allowed to return None
representing that the synthesis method is unable to synthesize the given higher-level-object. The actual synthesis of higher-level objects is performed by HighLevelSynthesis
transpiler pass. In the near future, HighLevelSynthesisPlugin
will be extended with additional information necessary to run this transpiler pass, for instance whether the plugin supports and/or requires coupling_map
to perform synthesis. For the full details refer to the HighLevelSynthesisPlugin
documentation for all the required fields. An example plugin class would look something like:
from qiskit.transpiler.passes.synthesis.plugin import HighLevelSynthesisPlugin
from qiskit.synthesis.clifford import synth_clifford_bm
class SpecialSynthesisClifford(HighLevelSynthesisPlugin):
def run(self, high_level_object, **options):
if higher_level_object.num_qubits <= 3:
return synth_clifford_bm(high_level_object)
else:
return None
The above example creates a plugin to synthesize objects of type Clifford that have at most 3 qubits, using the method ``synth_clifford_bm`
.
The second step is to expose the HighLevelSynthesisPlugin
as a setuptools entry point in the package metadata. This is done by adding an entry_points
entry to the setuptools.setup
call in the setup.py
for the plugin package with the necessary entry points under the qiskit.synthesis
namespace. For example:
entry_points = {
'qiskit.synthesis': [
'clifford.special = qiskit_plugin_pkg.module.plugin:SpecialSynthesisClifford',
]
},
(note that the entry point name = path
is a single string not a Python expression). The name
consists of two parts separated by dot “.”: the name of the type of Operation
to which the synthesis plugin applies (clifford
), and the name of the plugin (special
). There isn’t a limit to the number of plugins a single package can include as long as each plugin has a unique name.
Using Plugins
To use a plugin all you need to do is install the package that includes a synthesis plugin. Then Qiskit will automatically discover the installed plugins and expose them as valid options for the appropriate transpile()
kwargs and pass constructors. If there are any installed plugins which can’t be loaded/imported this will be logged to Python logging.
To get the installed list of installed unitary synthesis plugins you can use the qiskit.transpiler.passes.synthesis.plugin.unitary_synthesis_plugin_names()
function.
Plugin API
Unitary Synthesis Plugins
UnitarySynthesisPlugin () | Abstract unitary synthesis plugin class |
UnitarySynthesisPluginManager () | Unitary Synthesis plugin manager class |
unitary_synthesis_plugin_names () | Return a list of installed unitary synthesis plugin names |
High-Level Synthesis Plugins
HighLevelSynthesisPlugin () | Abstract high-level synthesis plugin class. |
HighLevelSynthesisPluginManager () | Class tracking the installed high-level-synthesis plugins. |