Source code for pennylane.templates.layer

# Copyright 2018-2021 Xanadu Quantum Technologies Inc.

# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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Contains the ``layer`` template constructor.
# pylint: disable-msg=too-many-branches,too-many-arguments,protected-access
from pennylane.math import shape

def _preprocess(args, depth):
    """Validate and pre-process inputs as follows:

    * Check that the dimension of the arguments corresponds to the depth

        args (tensor_like): trainable parameters of the template
        depth (int): how often the layer is repeated

    for arg in args:
        # some TF objects don't have len
        arg_depth = len(arg) if hasattr(arg, "__len__") else shape(arg)[0]
        if arg_depth != depth:
            raise ValueError(
                f"Each positional argument must have length matching 'depth'; expected {depth} got {arg_depth}"

[docs]def layer(template, depth, *args, **kwargs): r"""Repeatedly applies a unitary a given number of times. Args: template (callable): The sequence of quantum gates that is being repeated. This could be a single gate, a function of gates, or a "registered" PennyLane template. depth (int): The number of times the unitary is repeatedly applied. *args: Dynamic parameters that are passed into the unitary each time it is repeated. Each dynamic argument must be a list of first dimension equal to ``depth``. The :math:`j`-th element of the list is the value of the argument the :math:`j`-th time the unitary is applied. **kwargs: Static parameters that are passed into the unitary each time it is repeated. See usage details for more information. .. details:: :title: Usage Details **Layering Gates** The layering function can be used to repeatedly apply a function containing quantum operations, a template, or a quantum gate. For example, we can define the following subroutine: .. code-block:: python3 import pennylane as qml import numpy as np def subroutine(): qml.Hadamard(wires=[0]) qml.CNOT(wires=[0, 1]) qml.X(1) and then pass it into the ``qml.layer`` function. In this instance, we repeat ``subroutine`` three times: .. code-block:: python3 dev = qml.device('default.qubit', wires=3) @qml.qnode(dev) def circuit(): qml.layer(subroutine, 3) return [qml.expval(qml.Z(0)), qml.expval(qml.Z(1))] This creates the following circuit: >>> print(qml.draw(circuit)()) 0: ──H─╭●──H─╭●──H─╭●────┤ <Z> 1: ────╰X──X─╰X──X─╰X──X─┤ <Z> **Static Arguments** Static arguments are arguments passed into ``template`` that don't change with each repetition. Static parameters are always passed as keyword arguments into ``qml.layer``. For example, consider the following subroutine: .. code-block:: python3 def subroutine(wires): qml.Hadamard(wires=wires[0]) qml.CNOT(wires=wires) qml.X(wires[1]) We wish to repeat this gate sequence three times on wires ``1`` and ``2``. Since the wires on which the subroutine acts don't change with each repetition, the ``wires`` parameter is passed as a keyword argument. Therefore, we define a circuit as: .. code-block:: python3 @qml.qnode(dev) def circuit(): qml.layer(subroutine, 3, wires=[1, 2]) return [qml.expval(qml.Z(1)), qml.expval(qml.Z(2))] which yields the following circuit: >>> print(qml.draw(circuit)()) 1: ──H─╭●──H─╭●──H─╭●────┤ <Z> 2: ────╰X──X─╰X──X─╰X──X─┤ <Z> **Dynamic Arguments** In addition to passing static arguments to ``template``, we can also pass dynamic arguments. These are arguments that change with each repetition of the unitary. They are passed as non-keyword arguments to ``qml.layer``, after ``template`` and ``depth``. Each dynamic parameter must be a list of length equal to ``depth``. The :math:`j`-th element of the list represents the value of the argument used for the :math:`j`-th repetition. For example, let us define the following variational ansatz: .. code-block:: python3 def ansatz(params): qml.RX(params[0], wires=[0]) qml.MultiRZ(params[1], wires=[0, 1]) qml.RY(params[2], wires=[1]) We wish to repeat this ansatz two times, with each layer having different ``params``: .. code-block:: python3 @qml.qnode(dev) def circuit(params): qml.layer(ansatz, 2, params) return [qml.expval(qml.Z(0)), qml.expval(qml.Z(1))] Since we only have one dynamic argument, ``params``, we pass an array of first-dimension two, for the two layers of the repeated ansatz. We can also see that the ``params`` argument supplies three different parameters to three different gates. We therefore supply an array of size (2, 3) as an argument to ``qml.layer``: .. code-block:: python3 params = np.array([[0.5, 0.5, 0.5], [0.4, 0.4, 0.4]]) which yields the following circuit: >>> print(qml.draw(circuit)(params)) 0: ──RX(0.50)─╭MultiRZ(0.50)──RX(0.40)─╭MultiRZ(0.40)───────────┤ <Z> 1: ───────────╰MultiRZ(0.50)──RY(0.50)─╰MultiRZ(0.40)──RY(0.40)─┤ <Z> **Passing Multiple Static and Dynamic Arguments** It is also possible to pass multiple static and dynamic arguments into the same unitary. Dynamic arguments must be ordered in ``qml.layer`` in the same order in which they are passed into the ``template``. Consider the following ansatz: .. code-block:: python3 def ansatz(param1, param2, wires, var): qml.RX(param1, wires=wires[0]) qml.MultiRZ(param2, wires=wires) if var: qml.Hadamard(wires=wires[1]) This circuit can be repeated as: .. code-block:: python3 @qml.qnode(dev) def circuit(param1, param2): qml.layer(ansatz, 2, param1, param2, wires=[1, 2], var=True) return [qml.expval(qml.Z(1)), qml.expval(qml.Z(2))] We can then run the circuit with a given set of parameters (note that the parameters are of size (2, 1), as the circuit is repeated twice, and for each repetition, both ``param1`` and ``param2`` are simply real numbers): .. code-block:: python3 param1 = np.array([0.1, 0.2]) param2 = np.array([0.3, 0.4]) This gives us the following circuit: >>> print(qml.draw(circuit)(param1, param2)) 1: ──RX(0.10)─╭MultiRZ(0.30)──RX(0.20)─╭MultiRZ(0.40)────┤ <Z> 2: ───────────╰MultiRZ(0.30)──H────────╰MultiRZ(0.40)──H─┤ <Z> """ _preprocess(args, depth) for i in range(0, int(depth)): arg_params = [k[i] for k in args] template(*arg_params, **kwargs)