Add support for v2 provider interface (qiskit-community/qiskit-aqua#1270)

* Add support for v2 provider interface

In Qiskit/qiskit#5086 the v2 provider interface is being added.
This starter interface is basically a drop in replacement for the v1
interface with 3 changes it's explicitly versioned at the object level,
Backend.run() can take in a circuit object, and Job objects can also be
async or sync. Eventually the interace will likely evolve towards a
model similar to what was initially done in Qiskit/qiskit#4885.
This commit adds initial support for v2 provider backend objects, the
explicit type checking for BaseBackend objects is blocking the terra PR
from moving forward (because it switched BasicAer to use the v2
interface). This initial support just means accepting v2 Backend objects
in addition to v1 BaseBackend objects.

Depends on Qiskit/qiskit#5086

* Fix import path

* fix style

Co-authored-by: Manoel Marques <[email protected]>

Author: mtreinish

qiskit/aqua/algorithms/classifiers/qsvm/qsvm.py

@@ -23,6 +23,7 @@
 from qiskit.tools.events import TextProgressBar
 from qiskit.circuit import ParameterVector
 from qiskit.providers import BaseBackend
+from qiskit.providers import Backend
 from qiskit.aqua import QuantumInstance, aqua_globals
 from qiskit.aqua.algorithms import QuantumAlgorithm
 from qiskit.aqua import AquaError
@@ -79,7 +80,8 @@ def __init__(self, feature_map: Union[QuantumCircuit, FeatureMap],
                  test_dataset: Optional[Dict[str, np.ndarray]] = None,
                  datapoints: Optional[np.ndarray] = None,
                  multiclass_extension: Optional[MulticlassExtension] = None,
-                 quantum_instance: Optional[Union[QuantumInstance, BaseBackend]] = None) -> None:
+                 quantum_instance: Optional[
+                     Union[QuantumInstance, BaseBackend, Backend]] = None) -> None:
         """
         Args:
             feature_map: Feature map module, used to transform data

qiskit/aqua/algorithms/classifiers/vqc.py

@@ -23,6 +23,7 @@
 from qiskit.circuit import ParameterVector, ParameterExpression
 
 from qiskit.providers import BaseBackend
+from qiskit.providers import Backend
 from qiskit.aqua import QuantumInstance, AquaError, aqua_globals
 from qiskit.aqua.utils import map_label_to_class_name
 from qiskit.aqua.utils import split_dataset_to_data_and_labels
@@ -64,7 +65,8 @@ def __init__(
             max_evals_grouped: int = 1,
             minibatch_size: int = -1,
             callback: Optional[Callable[[int, np.ndarray, float, int], None]] = None,
-            quantum_instance: Optional[Union[QuantumInstance, BaseBackend]] = None) -> None:
+            quantum_instance: Optional[
+                Union[QuantumInstance, BaseBackend, Backend]] = None) -> None:
         """
         Args:
             optimizer: The classical optimizer to use.

qiskit/aqua/algorithms/distribution_learners/qgan.py

@@ -22,6 +22,7 @@
 
 from qiskit.circuit import QuantumCircuit
 from qiskit.providers import BaseBackend
+from qiskit.providers import Backend
 from qiskit.aqua import QuantumInstance, AquaError, aqua_globals
 from qiskit.aqua.algorithms import QuantumAlgorithm
 from qiskit.aqua.components.neural_networks.discriminative_network import DiscriminativeNetwork
@@ -69,7 +70,8 @@ def __init__(self, data: np.ndarray, bounds: Optional[np.ndarray] = None,
                  discriminator: Optional[DiscriminativeNetwork] = None,
                  generator: Optional[GenerativeNetwork] = None,
                  tol_rel_ent: Optional[float] = None, snapshot_dir: Optional[str] = None,
-                 quantum_instance: Optional[Union[QuantumInstance, BaseBackend]] = None) -> None:
+                 quantum_instance: Optional[
+                     Union[QuantumInstance, BaseBackend, Backend]] = None) -> None:
         """
 
         Args: