qml.workflow.get_transform_program¶
-
get_transform_program
(qnode, level=None)[source]¶ Extract a transform program at a designated level.
- Parameters
qnode (QNode) – the qnode to get the transform program for.
level (None, str, int, slice) –
And indication of what transforms to use from the full program.
None
: use the full transform programstr
: Acceptable keys are"user"
,"device"
,"top"
and"gradient"
int
: How many transforms to include, starting from the front of the programslice
: a slice to select out components of the transform program.
- Returns
the transform program corresponding to the requested level.
- Return type
Usage Details
The transforms are organized as:
where
transform1
is first applied to theQNode
followed bytransform2
. First user transforms are run on the tapes, followed by the gradient expansion, followed by the device expansion. “Final” transforms, likeparam_shift
andmetric_tensor
, always occur at the end of the program.dev = qml.device('default.qubit') @qml.metric_tensor # final transform @qml.transforms.merge_rotations # transform 2 @qml.transforms.cancel_inverses # transform 1 @qml.qnode(dev, diff_method="parameter-shift", shifts=np.pi / 4) def circuit(): return qml.expval(qml.Z(0))
By default, we get the full transform program. This can be manually specified by
level=None
.>>> qml.workflow.get_transform_program(circuit) TransformProgram(cancel_inverses, merge_rotations, _expand_metric_tensor, _expand_transform_param_shift, validate_device_wires, defer_measurements, decompose, validate_measurements, validate_observables, metric_tensor)
The
"user"
transforms are the ones manually applied to the qnode,cancel_inverses
andmerge_rotations
.>>> qml.workflow.get_transform_program(circuit, level="user") TransformProgram(cancel_inverses, merge_rotations)
The
_expand_transform_param_shift
is the"gradient"
transform. This expands all trainable operations to a state where the parameter shift transform can operate on them. For example, it will decompose any parametrized templates into operators that have generators.>>> qml.workflow.get_transform_program(circuit, level="gradient") TransformProgram(cancel_inverses, merge_rotations, _expand_transform_param_shift)
"device"
includes all transforms except for a"final"
transform, if it exists. This usually corresponds to the circuits that will be sent to the device to execute.>>> qml.workflow.get_transform_program(circuit, level="device") TransformProgram(cancel_inverses, merge_rotations, _expand_transform_param_shift, validate_device_wires, defer_measurements, decompose, validate_measurements, validate_observables)
"top"
and0
both return empty transform programs.>>> qml.workflow.get_transform_program(circuit, level="top") TransformProgram() >>> qml.workflow.get_transform_program(circuit, level=0) TransformProgram()
The
level
can also be any integer, corresponding to a number of transforms in the program.>>> qml.workflow.get_transform_program(circuit, level=2) TransformProgram(cancel_inverses, merge_rotations)
level
can also accept aslice
object to select out any arbitrary subset of the transform program. This allows you to select different starting transforms or strides. For example, you can skip the first transform or reverse the order:>>> qml.workflow.get_transform_program(circuit, level=slice(1,3)) TransformProgram(merge_rotations, _expand_transform_param_shift) >>> qml.workflow.get_transform_program(circuit, level=slice(None, None, -1)) TransformProgram(metric_tensor, validate_observables, validate_measurements, decompose, defer_measurements, validate_device_wires, _expand_transform_param_shift, _expand_metric_tensor, merge_rotations, cancel_inverses)