Quantum Kernel

.pylintdict

@@ -29,6 +29,7 @@ hashable
 hoc
 innerproduct
 kwargs
+langle
 ldots
 len
 maxiter
@@ -45,7 +46,9 @@ np
 numpy
 nxd
 nxk
+nxm
 nxn
+mxd
 opflow
 optim
 optimizer's
@@ -55,6 +58,7 @@ parameterexpression
 parametrized
 params
 pca
+precomputed
 probs
 py
 pytorch
@@ -65,28 +69,37 @@ qiskit
 qiskit's
 qnn
 qp
+qsvc
+qsvr
 qubit
 qubits
+rangle
 rbf
 readme
+Regressor
+Regressors
 renormalize
 scikit
 scipy
+semidefinite
 sigmoid
 sklearn
 statevector
 statevectors
 stdout
 str
 submodules
+SVC
 svm
+SVR
 sx
 sy
 terra
 toctree
 todo
 transpile
 univariate
+unsymmetric
 utils
 varform
 variational

docs/apidocs/qiskit_machine_learning.kernels.rst

@@ -0,0 +1,6 @@
+.. _qiskit-machine-learning-kernels:
+
+.. automodule:: qiskit_machine_learning.kernels
+   :no-members:
+   :no-inherited-members:
+   :no-special-members:

docs/conf.py

@@ -67,6 +67,7 @@
     'sphinx_autodoc_typehints',
     'reno.sphinxext',
     'sphinx.ext.doctest',
+    'sphinx.ext.intersphinx',
 ]
 html_static_path = ['_static']
 templates_path = ['_templates']
@@ -148,3 +149,7 @@
 }
 
 autoclass_content = 'both'
+
+intersphinx_mapping = {
+    'sklearn': ('https://scikit-learn.org/stable', None),
+}

qiskit_machine_learning/__init__.py

@@ -37,6 +37,7 @@
    algorithms
    circuit.library
    datasets
+   kernels
    neural_networks
 
 """

qiskit_machine_learning/algorithms/__init__.py

@@ -26,8 +26,19 @@
    :toctree: ../stubs/
    :nosignatures:
 
+   QSVC
    VQC
 
+Regressors
+++++++++++
+Quantum Support Vector Regressor.
+
+.. autosummary::
+   :toctree: ../stubs/
+   :nosignatures:
+
+   QSVR
+
 Distribution Learners
 +++++++++++++++++++++
 
@@ -44,15 +55,18 @@
 
 """
 
-from .classifiers import VQC
+from .classifiers import QSVC, VQC
+from .regressors import QSVR
 from .distribution_learners import (DiscriminativeNetwork,
                                     GenerativeNetwork,
                                     NumPyDiscriminator,
                                     PyTorchDiscriminator,
                                     QuantumGenerator, QGAN)
 
 __all__ = [
+    'QSVC',
     'VQC',
+    'QSVR',
     'DiscriminativeNetwork',
     'GenerativeNetwork',
     'NumPyDiscriminator',

qiskit_machine_learning/algorithms/classifiers/__init__.py

@@ -12,8 +12,10 @@
 
 """ Classifiers Package """
 
+from .qsvc import QSVC
 from .vqc import VQC
 
 __all__ = [
+    'QSVC',
     'VQC'
 ]

qiskit_machine_learning/algorithms/classifiers/qsvc.py

@@ -0,0 +1,63 @@
+# This code is part of Qiskit.
+#
+# (C) Copyright IBM 2021.
+#
+# This code is licensed under the Apache License, Version 2.0. You may
+# obtain a copy of this license in the LICENSE.txt file in the root directory
+# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
+#
+# Any modifications or derivative works of this code must retain this
+# copyright notice, and modified files need to carry a notice indicating
+# that they have been altered from the originals.
+
+"""Quantum Support Vector Classifier"""
+import logging
+
+from typing import Optional
+
+from sklearn.svm import SVC
+
+from qiskit_machine_learning.kernels.quantum_kernel import QuantumKernel
+
+logger = logging.getLogger(__name__)
+
+
+class QSVC(SVC):
+    r"""Quantum Support Vector Classifier.
+
+    This class shows how to use a quantum kernel for classification. The class extends
+    `sklearn.svm.SVC <https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html>`_,
+    and thus inherits its methods like ``fit`` and ``predict`` used in the example below.
+    Read more in the
+    `sklearn user guide <https://scikit-learn.org/stable/modules/svm.html#svm-classification>`_.
+
+    **Example**
+
+    .. code-block::
+
+        qsvc = QSVC(quantum_kernel=qkernel)
+        qsvc.fit(sample_train,label_train)
+        qsvc.predict(sample_test)
+    """
+
+    def __init__(self, *args,
+                 quantum_kernel: Optional[QuantumKernel] = None, **kwargs):
+        """
+        Args:
+            quantum_kernel: QuantumKernel to be used for classification.
+        """
+
+        self._quantum_kernel = quantum_kernel if quantum_kernel else QuantumKernel()
+
+        super().__init__(kernel=self._quantum_kernel.evaluate, *args, **kwargs)
+
+    @property
+    def quantum_kernel(self) -> QuantumKernel:
+        """ Returns quantum kernel """
+        return self._quantum_kernel
+
+    @quantum_kernel.setter
+    def quantum_kernel(self, quantum_kernel: QuantumKernel):
+        """ Sets quantum kernel """
+        self._quantum_kernel = quantum_kernel
+        self.kernel = self._quantum_kernel

qiskit_machine_learning/algorithms/regressors/__init__.py

@@ -0,0 +1,19 @@
+# This code is part of Qiskit.
+#
+# (C) Copyright IBM 2021.
+#
+# This code is licensed under the Apache License, Version 2.0. You may
+# obtain a copy of this license in the LICENSE.txt file in the root directory
+# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
+#
+# Any modifications or derivative works of this code must retain this
+# copyright notice, and modified files need to carry a notice indicating
+# that they have been altered from the originals.
+
+""" Regressors Package"""
+
+from .qsvr import QSVR
+
+__all__ = [
+    'QSVR'
+]

qiskit_machine_learning/algorithms/regressors/qsvr.py

@@ -0,0 +1,63 @@
+# This code is part of Qiskit.
+#
+# (C) Copyright IBM 2021.
+#
+# This code is licensed under the Apache License, Version 2.0. You may
+# obtain a copy of this license in the LICENSE.txt file in the root directory
+# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
+#
+# Any modifications or derivative works of this code must retain this
+# copyright notice, and modified files need to carry a notice indicating
+# that they have been altered from the originals.
+
+"""Quantum Support Vector Regressor"""
+import logging
+
+from typing import Optional
+
+from sklearn.svm import SVR
+
+from ...kernels.quantum_kernel import QuantumKernel
+
+logger = logging.getLogger(__name__)
+
+
+class QSVR(SVR):
+    r"""Quantum Support Vector Regressor.
+
+    This class shows how to use a quantum kernel for classification. The class extends
+    `sklearn.svm.SVR <https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVR.html>`_,
+    and thus inherits its methods like ``fit`` and ``predict`` used in the example below.
+    Read more in the
+    `sklearn user guide <https://scikit-learn.org/stable/modules/svm.html#svm-regression>`_.
+
+    **Example**
+
+    .. code-block::
+
+        qsvr = QSVR(quantum_kernel=qkernel)
+        qsvr.fit(sample_train,label_train)
+        qsvr.predict(sample_test)
+    """
+
+    def __init__(self, *args,
+                 quantum_kernel: Optional[QuantumKernel] = None, **kwargs):
+        """
+        Args:
+            quantum_kernel: QuantumKernel to be used for classification.
+        """
+
+        self._quantum_kernel = quantum_kernel if quantum_kernel else QuantumKernel()
+
+        super().__init__(kernel=self._quantum_kernel.evaluate, *args, **kwargs)
+
+    @property
+    def quantum_kernel(self) -> QuantumKernel:
+        """ Returns quantum kernel """
+        return self._quantum_kernel
+
+    @quantum_kernel.setter
+    def quantum_kernel(self, quantum_kernel: QuantumKernel):
+        """ Sets quantum kernel """
+        self._quantum_kernel = quantum_kernel
+        self.kernel = self._quantum_kernel

qiskit_machine_learning/kernels/__init__.py

@@ -0,0 +1,33 @@
+# This code is part of Qiskit.
+#
+# (C) Copyright IBM 2021.
+#
+# This code is licensed under the Apache License, Version 2.0. You may
+# obtain a copy of this license in the LICENSE.txt file in the root directory
+# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
+#
+# Any modifications or derivative works of this code must retain this
+# copyright notice, and modified files need to carry a notice indicating
+# that they have been altered from the originals.
+
+"""
+Quantum Kernels (:mod:`qiskit_machine_learning.kernels`)
+
+.. currentmodule:: qiskit_machine_learning.kernels
+
+Quantum Kernels
+===============
+
+.. autosummary::
+   :toctree: ../stubs/
+   :nosignatures:
+
+   QuantumKernel
+
+"""
+
+from .quantum_kernel import QuantumKernel
+
+__all__ = [
+    'QuantumKernel'
+]