qml.transforms.core.transform_program.TransformProgram

class TransformProgram(initial_program=None, cotransform_cache=None)

Bases: object

Class that contains a transform program and the methods to interact with it.

The order of execution is the order in the list containing the containers.

Parameters

• initial_program (Optional[Sequence[TransformContainer]]) – A sequence of transforms with which to initialize the program.

• cotransform_cache (Optional[CotransformCache]) – A named tuple containing the qnode, args, and kwargs required to compute classical cotransforms.

The main case where one would have to interact directly with a transform program is when developing a Device. In this case, the pre-processing method of a device returns a transform program. You should directly refer to the device API documentation for more details.

Warning

This class is developer-facing and should not be used directly. Instead, use qml.transform if you would like to make a custom transform.

See also

transform()

Implemented Dunder methods

Programs have several implemented dunder methods for easy manipulation.

>>> from pennylane.transforms.core.transform_program import TransformProgram
>>> from copy import copy
>>> program = TransformProgram()
>>> program.add_transform(qml.compile)
>>> program.add_transform(qml.transforms.cancel_inverses)
>>> [t for t in program]  # Iteration
[<compile([], {})>, <cancel_inverses([], {})>]
>>> program[0]
<compile([], {})>
>>> program[::-1]
TransformProgram(cancel_inverses, compile)
>>> len(program)
2
>>> True if program else False
True
>>> True if TransformProgram() else False
False
>>> program2 = copy(program)
>>> program2 == program
True
>>> qml.compile in program
True
>>> qml.transforms.split_non_commuting in program
False
>>> program + program
TransformProgram(compile, cancel_inverses, compile, cancel_inverses)

Attributes

has_final_transform	True if the transform program has a terminal transform.
is_informative	True if the transform program is informative.

has_final_transform

True if the transform program has a terminal transform.

is_informative

True if the transform program is informative.

Returns

Boolean

Return type

bool

Methods

add_transform(transform, *targs, **tkwargs)	Add a transform (dispatcher) to the end of the program.
get_last()	Get the last transform container.
has_classical_cotransform()	Check if the transform program has some classical cotransforms.
insert_front(transform_container)	Insert the transform container at the beginning of the program.
insert_front_transform(transform, *targs, ...)	Add a transform (dispatcher) to the beginning of the program.
is_empty()	Check if the transform program is empty or not.
pop_front()	Pop the transform container at the beginning of the program.
prune_dynamic_transform([type_to_keep])	Ensures that only one or none dynamic_one_shot is applied.
push_back(transform_container)	Add a transform (container) to the end of the program.
set_classical_component(qnode, args, kwargs)	Set the classical jacobians and argnums if the transform is hybrid with a classical cotransform.

add_transform(transform, *targs, **tkwargs)

Add a transform (dispatcher) to the end of the program.

Note that this should be a function decorated with/called by qml.transforms.transform, and not a TransformContainer.

Parameters

• transform (TransformDispatcher) – The transform to add to the transform program.

• *targs – Any additional arguments that are passed to the transform.

Keyword Arguments

**tkwargs – Any additional keyword arguments that are passed to the transform.

get_last()

Get the last transform container.

Returns

The last transform in the program.

Return type

TransformContainer

Raises

TransformError – It raises an error if the program is empty.

has_classical_cotransform()

Check if the transform program has some classical cotransforms.

Returns

Boolean

Return type

bool

insert_front(transform_container)

Insert the transform container at the beginning of the program.

Parameters

transform_container (TransformContainer) – A transform represented by its container.

insert_front_transform(transform, *targs, **tkwargs)

Add a transform (dispatcher) to the beginning of the program.

Parameters

• transform (TransformDispatcher) – The transform to add to the front of the transform program.

• *targs – Any additional arguments that are passed to the transform.

Keyword Arguments

**tkwargs – Any additional keyword arguments that are passed to the transform.

is_empty()

Check if the transform program is empty or not.

Returns

Boolean, True if empty, False otherwise.

Return type

bool

pop_front()

Pop the transform container at the beginning of the program.

Returns

The transform container at the beginning of the program.

Return type

TransformContainer

prune_dynamic_transform(type_to_keep=1)

Ensures that only one or none dynamic_one_shot is applied.

Parameters

type_to_keep (int) – The type of the dynamic transform to keep. 0: keep none, 1: dynamic_one_shot or mid_circuit_measurements, 2: only mid_circuit_measurements.

Returns

True if a dynamic transform was found, False otherwise.

Return type

bool

push_back(transform_container)

Add a transform (container) to the end of the program.

Parameters

transform_container (TransformContainer) – A transform represented by its container.

set_classical_component(qnode, args, kwargs)

Set the classical jacobians and argnums if the transform is hybrid with a classical cotransform.

code/api/pennylane.transforms.core.transform_program.TransformProgram

 

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