[WIP] Qubit mapping

[KetpuntoG]

Transform that maps a circuit to a specific architecture:

import pennylane as qml

graph = {"a": ["b"], "b": ["a", "c"], "c": ["b"]}
init_mapping = {0: "a", 1: "b", 2: "c"} # optional

dev = qml.device('default.qubit')

@partial(qml.transforms.qubit_mapping, graph = graph, init_mapping = init_mapping)
@qml.qnode(dev)
def circuit():
    qml.Hadamard(0)
    qml.CNOT([0, 2])
    return qml.expval(qml.Z(2))

print(qml.draw(circuit)())

a: ──H────╭●─┤
b: ─╭SWAP─╰X─┤  <Z>
c: ─╰SWAP────┤

The algorithm has been implemented following scalability as the main requirement.
Below is a comparison with Qiskit in time and CNOTs gates added in the routing for the case of an NxN grid architecture. In all grids we are applying 5000 two-qubit gates randomly

[github-actions]

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Please edit doc/releases/changelog-dev.md with:

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[codecov]

Codecov Report

Attention: Patch coverage is 88.00000% with 18 lines in your changes missing coverage. Please review.

Project coverage is 99.61%. Comparing base (31647e3) to head (bb5cac1).
Report is 36 commits behind head on master.

Files with missing lines	Patch %	Lines
pennylane/transforms/optimization/qubit_mapping.py	87.91%	18 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #7390      +/-   ##
==========================================
- Coverage   99.64%   99.61%   -0.04%     
==========================================
  Files         514      530      +16     
  Lines       50088    50762     +674     
==========================================
+ Hits        49912    50568     +656     
- Misses        176      194      +18     

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