Auto Commit

Author: Siddharthgolecha

qiskit_machine_learning/algorithms/classifiers/vqc.py

@@ -17,7 +17,7 @@
 import numpy as np
 
 from qiskit import QuantumCircuit
-from qiskit.primitives import BaseSampler
+from qiskit.primitives import BaseSamplerV2 # change: BaseSampler is migrated to BaseSamplerV2
 from qiskit.transpiler.passmanager import BasePassManager
 
 from ...neural_networks import SamplerQNN
@@ -27,7 +27,6 @@
 
 from .neural_network_classifier import NeuralNetworkClassifier
 
-
 class VQC(NeuralNetworkClassifier):
     r"""A convenient Variational Quantum Classifier implementation.
 
@@ -58,7 +57,7 @@ def __init__(
         initial_point: np.ndarray | None = None,
         callback: Callable[[np.ndarray, float], None] | None = None,
         *,
-        sampler: BaseSampler | None = None,
+        sampler: BaseSamplerV2 | None = None, # change: BaseSampler is migrated to BaseSamplerV2
         interpret: Callable[[int], int | tuple[int, ...]] | None = None,
         output_shape: int | None = None,
         pass_manager: BasePassManager | None = None,
@@ -198,4 +197,4 @@ def _get_interpret(self, num_classes: int):
         def parity(x: int, num_classes: int = num_classes) -> int:
             return x % num_classes
 
-        return parity
+        return parity

qiskit_machine_learning/algorithms/inference/qbayesian.py

@@ -20,13 +20,12 @@
 from qiskit.quantum_info import Statevector
 from qiskit.circuit import Qubit
 from qiskit.circuit.library import grover_operator
-from qiskit.primitives import BaseSampler, Sampler, BaseSamplerV2, BaseSamplerV1
+from qiskit.primitives import BaseSamplerV2, StatevectorSampler # change: BaseSampler and Sampler are replaced by BaseSamplerV2 and StatevectorSampler
 from qiskit.transpiler.passmanager import BasePassManager
 from qiskit.result import QuasiDistribution
 
 from ...utils.deprecation import issue_deprecation_msg
 
-
 class QBayesian:
     r"""
     Implements a quantum Bayesian inference (QBI) algorithm that has been developed in [1]. The
@@ -67,7 +66,7 @@ def __init__(
         *,
         limit: int = 10,
         threshold: float = 0.9,
-        sampler: BaseSampler | BaseSamplerV2 | None = None,
+        sampler: BaseSamplerV2 | None = None, # change: BaseSampler is replaced by BaseSamplerV2
         pass_manager: BasePassManager | None = None,
     ):
         """
@@ -96,9 +95,9 @@ def __init__(
         self._limit = limit
         self._threshold = threshold
         if sampler is None:
-            sampler = Sampler()
+            sampler = StatevectorSampler() # change: Sampler is replaced by StatevectorSampler
 
-        if isinstance(sampler, BaseSamplerV1):
+        if isinstance(sampler, BaseSamplerV2): # change: BaseSamplerV1 is replaced by BaseSamplerV2
             issue_deprecation_msg(
                 msg="V1 Primitives are deprecated",
                 version="0.8.0",
@@ -167,15 +166,15 @@ def _run_circuit(self, circuit: QuantumCircuit) -> Dict[str, float]:
         """Run the quantum circuit with the sampler."""
         counts = {}
 
-        if isinstance(self._sampler, BaseSampler):
+        if isinstance(self._sampler, BaseSamplerV2): # change: BaseSampler is replaced by BaseSamplerV2
             # Sample from circuit
             job = self._sampler.run(circuit)
             result = job.result()
 
             # Get the counts of quantum state results
             counts = result.quasi_dists[0].nearest_probability_distribution().binary_probabilities()
 
-        elif isinstance(self._sampler, BaseSamplerV2):
+        elif isinstance(self._sampler, BaseSamplerV2): # change: BaseSamplerV2 is replaced by BaseSamplerV2
             # Sample from circuit
             if self._pass_manager is not None:
                 circuit = self._pass_manager.run(circuit)
@@ -412,12 +411,12 @@ def limit(self, limit: int):
         self._limit = limit
 
     @property
-    def sampler(self) -> BaseSampler | BaseSamplerV2:
+    def sampler(self) -> BaseSamplerV2: # change: BaseSampler is replaced by BaseSamplerV2
         """Returns the sampler primitive used to compute the samples."""
         return self._sampler
 
     @sampler.setter
-    def sampler(self, sampler: BaseSampler | BaseSamplerV2):
+    def sampler(self, sampler: BaseSamplerV2): # change: BaseSampler is replaced by BaseSamplerV2
         """Set the sampler primitive used to compute the samples."""
         self._sampler = sampler
 
@@ -429,4 +428,4 @@ def threshold(self) -> float:
     @threshold.setter
     def threshold(self, threshold: float):
         """Set the threshold to accept the evidence."""
-        self._threshold = threshold
+        self._threshold = threshold

qiskit_machine_learning/algorithms/regressors/vqr.py

@@ -16,7 +16,7 @@
 
 import numpy as np
 from qiskit import QuantumCircuit
-from qiskit.primitives import BaseEstimator
+from qiskit.primitives import BaseEstimatorV2 # change: BaseEstimator is migrated to BaseEstimatorV2
 from qiskit.quantum_info.operators.base_operator import BaseOperator
 from qiskit.transpiler.passmanager import BasePassManager
 
@@ -26,7 +26,6 @@
 from ...utils import derive_num_qubits_feature_map_ansatz
 from ...utils.loss_functions import Loss
 
-
 class VQR(NeuralNetworkRegressor):
     """A convenient Variational Quantum Regressor implementation."""
 
@@ -43,7 +42,7 @@ def __init__(
         initial_point: np.ndarray | None = None,
         callback: Callable[[np.ndarray, float], None] | None = None,
         *,
-        estimator: BaseEstimator | None = None,
+        estimator: BaseEstimatorV2 | None = None, # change: BaseEstimator is migrated to BaseEstimatorV2
         pass_manager: BasePassManager | None = None,
     ) -> None:
         r"""
@@ -145,4 +144,4 @@ def ansatz(self) -> QuantumCircuit:
     @property
     def num_qubits(self) -> int:
         """Returns the number of qubits used by ansatz and feature map."""
-        return self._num_qubits
+        return self._num_qubits

qiskit_machine_learning/gradients/base/base_estimator_gradient.py

@@ -23,8 +23,7 @@
 import numpy as np
 
 from qiskit.circuit import Parameter, ParameterExpression, QuantumCircuit
-from qiskit.primitives import BaseEstimator, BaseEstimatorV1
-from qiskit.primitives.base import BaseEstimatorV2
+from qiskit.primitives import BaseEstimatorV2 # change: BaseEstimator is migrated to BaseEstimatorV2
 from qiskit.primitives.utils import _circuit_key
 from qiskit.providers import Options
 from qiskit.quantum_info.operators.base_operator import BaseOperator
@@ -42,13 +41,12 @@
 from ...utils.deprecation import issue_deprecation_msg
 from ...algorithm_job import AlgorithmJob
 
-
 class BaseEstimatorGradient(ABC):
     """Base class for an ``EstimatorGradient`` to compute the gradients of the expectation value."""
 
     def __init__(
         self,
-        estimator: BaseEstimator | BaseEstimatorV2,
+        estimator: BaseEstimatorV2, # change: BaseEstimator is migrated to BaseEstimatorV2
         options: Options | None = None,
         derivative_type: DerivativeType = DerivativeType.REAL,
         pass_manager: BasePassManager | None = None,
@@ -73,14 +71,7 @@ def __init__(
             pass_manager: The pass manager to transpile the circuits if necessary.
             Defaults to ``None``, as some primitives do not need transpiled circuits.
         """
-        if isinstance(estimator, BaseEstimatorV1):
-            issue_deprecation_msg(
-                msg="V1 Primitives are deprecated",
-                version="0.8.0",
-                remedy="Use V2 primitives for continued compatibility and support.",
-                period="4 months",
-            )
-        self._estimator: BaseEstimator = estimator
+        self._estimator: BaseEstimatorV2 = estimator # change: BaseEstimator is migrated to BaseEstimatorV2
         self._pass_manager = pass_manager
         self._default_options = Options()
         if options is not None:
@@ -373,4 +364,4 @@ def _get_local_options(self, options: Options) -> Options:
         """
         opts = copy(self._estimator.options)
         opts.update_options(**options)
-        return opts
+        return opts

qiskit_machine_learning/gradients/base/base_sampler_gradient.py

@@ -22,7 +22,7 @@
 from copy import copy
 
 from qiskit.circuit import Parameter, ParameterExpression, QuantumCircuit
-from qiskit.primitives import BaseSampler, BaseSamplerV1
+from qiskit.primitives import BaseSamplerV2, BaseSamplerV1 # change: BaseSampler is migrated to BaseSamplerV2
 from qiskit.primitives.utils import _circuit_key
 from qiskit.providers import Options
 from qiskit.transpiler.passes import TranslateParameterizedGates
@@ -38,13 +38,12 @@
 from ...utils.deprecation import issue_deprecation_msg
 from ...algorithm_job import AlgorithmJob
 
-
 class BaseSamplerGradient(ABC):
     """Base class for a ``SamplerGradient`` to compute the gradients of the sampling probability."""
 
     def __init__(
         self,
-        sampler: BaseSampler,
+        sampler: BaseSamplerV2, # change: BaseSampler is migrated to BaseSamplerV2
         options: Options | None = None,
         pass_manager: BasePassManager | None = None,
     ):
@@ -65,7 +64,7 @@ def __init__(
                 remedy="Use V2 primitives for continued compatibility and support.",
                 period="4 months",
             )
-        self._sampler: BaseSampler = sampler
+        self._sampler: BaseSamplerV2 = sampler # change: BaseSampler is migrated to BaseSamplerV2
         self._pass_manager = pass_manager
         self._default_options = Options()
         if options is not None:
@@ -313,4 +312,4 @@ def _get_local_options(self, options: Options) -> Options:
         """
         opts = copy(self._sampler.options)
         opts.update_options(**options)
-        return opts
+        return opts

qiskit_machine_learning/gradients/lin_comb/lin_comb_estimator_gradient.py

@@ -20,7 +20,7 @@
 
 from qiskit.circuit import Parameter, QuantumCircuit
 from qiskit.primitives.base import BaseEstimatorV2
-from qiskit.primitives import BaseEstimator, BaseEstimatorV1
+from qiskit.primitives import BaseEstimatorV1, BaseEstimatorV2 # change: BaseEstimator is migrated to BaseEstimatorV2
 from qiskit.transpiler.passmanager import BasePassManager
 
 from qiskit.primitives.utils import init_observable, _circuit_key
@@ -33,7 +33,6 @@
 
 from ...exceptions import AlgorithmError
 
-
 class LinCombEstimatorGradient(BaseEstimatorGradient):
     """Compute the gradients of the expectation values.
     This method employs a linear combination of unitaries [1].
@@ -68,7 +67,7 @@ class LinCombEstimatorGradient(BaseEstimatorGradient):
 
     def __init__(
         self,
-        estimator: BaseEstimator,
+        estimator: BaseEstimatorV2, # change: BaseEstimator is migrated to BaseEstimatorV2
         derivative_type: DerivativeType = DerivativeType.REAL,
         options: Options | None = None,
         pass_manager: BasePassManager | None = None,
@@ -245,4 +244,4 @@ def _run_unique(
                 + f"{type(self._estimator)} instead. Note that BaseEstimatorV1 is deprecated in"
                 + "Qiskit and removed in Qiskit IBM Runtime."
             )
-        return EstimatorGradientResult(gradients=gradients, metadata=metadata, options=opt)
+        return EstimatorGradientResult(gradients=gradients, metadata=metadata, options=opt)

qiskit_machine_learning/gradients/lin_comb/lin_comb_sampler_gradient.py

@@ -21,8 +21,7 @@
 from qiskit.circuit import Parameter, QuantumCircuit
 from qiskit.primitives.utils import _circuit_key
 
-from qiskit.primitives import BaseSampler, BaseSamplerV1
-from qiskit.primitives.base import BaseSamplerV2
+from qiskit.primitives import BaseSamplerV1, BaseSamplerV2 # change: BaseSampler is migrated to BaseSamplerV2
 from qiskit.result import QuasiDistribution
 from qiskit.providers import Options
 from qiskit.transpiler.passmanager import BasePassManager
@@ -33,7 +32,6 @@
 
 from ...exceptions import AlgorithmError
 
-
 class LinCombSamplerGradient(BaseSamplerGradient):
     """Compute the gradients of the sampling probability.
     This method employs a linear combination of unitaries [1].
@@ -68,7 +66,7 @@ class LinCombSamplerGradient(BaseSamplerGradient):
 
     def __init__(
         self,
-        sampler: BaseSampler,
+        sampler: BaseSamplerV2, # change: BaseSampler is migrated to BaseSamplerV2
         options: Options | None = None,
         pass_manager: BasePassManager | None = None,
     ):
@@ -190,4 +188,4 @@ def _run_unique(
             gradients.append(gradient)
             partial_sum_n += n
 
-        return SamplerGradientResult(gradients=gradients, metadata=metadata, options=opt)
+        return SamplerGradientResult(gradients=gradients, metadata=metadata, options=opt)

qiskit_machine_learning/gradients/spsa/spsa_estimator_gradient.py

@@ -22,15 +22,14 @@
 from qiskit.providers import Options
 from qiskit.quantum_info.operators.base_operator import BaseOperator
 from qiskit.primitives.base import BaseEstimatorV2
-from qiskit.primitives import BaseEstimator, BaseEstimatorV1
+from qiskit.primitives import BaseEstimatorV2, BaseEstimatorV1 # change: BaseEstimator is migrated to BaseEstimatorV2
 from qiskit.transpiler.passmanager import BasePassManager
 
 from ..base.base_estimator_gradient import BaseEstimatorGradient
 from ..base.estimator_gradient_result import EstimatorGradientResult
 
 from ...exceptions import AlgorithmError
 
-
 class SPSAEstimatorGradient(BaseEstimatorGradient):
     """
     Compute the gradients of the expectation value by the Simultaneous Perturbation Stochastic
@@ -45,7 +44,7 @@ class SPSAEstimatorGradient(BaseEstimatorGradient):
     # pylint: disable=too-many-positional-arguments
     def __init__(
         self,
-        estimator: BaseEstimator,
+        estimator: BaseEstimatorV2, # change: BaseEstimator is migrated to BaseEstimatorV2
         epsilon: float = 1e-6,
         batch_size: int = 1,
         seed: int | None = None,
@@ -187,4 +186,4 @@ def _run(
                 + "Qiskit and removed in Qiskit IBM Runtime."
             )
 
-        return EstimatorGradientResult(gradients=gradients, metadata=metadata, options=opt)
+        return EstimatorGradientResult(gradients=gradients, metadata=metadata, options=opt)

qiskit_machine_learning/gradients/spsa/spsa_sampler_gradient.py

@@ -21,8 +21,7 @@
 
 from qiskit.circuit import Parameter, QuantumCircuit
 
-from qiskit.primitives import BaseSampler, BaseSamplerV1
-from qiskit.primitives.base import BaseSamplerV2
+from qiskit.primitives import BaseSamplerV1, BaseSamplerV2 # change: BaseSampler is migrated to BaseSamplerV2
 from qiskit.result import QuasiDistribution
 from qiskit.providers import Options
 from qiskit.transpiler.passmanager import BasePassManager
@@ -32,7 +31,6 @@
 
 from ...exceptions import AlgorithmError
 
-
 class SPSASamplerGradient(BaseSamplerGradient):
     """
     Compute the gradients of the sampling probability by the Simultaneous Perturbation Stochastic
@@ -47,7 +45,7 @@ class SPSASamplerGradient(BaseSamplerGradient):
     # pylint: disable=too-many-positional-arguments
     def __init__(
         self,
-        sampler: BaseSampler,
+        sampler: BaseSamplerV2, # change: BaseSampler is migrated to BaseSamplerV2
         epsilon: float = 1e-6,
         batch_size: int = 1,
         seed: int | None = None,
@@ -176,4 +174,4 @@ def _run(
             gradients.append(gradient)
             partial_sum_n += n
 
-        return SamplerGradientResult(gradients=gradients, metadata=metadata, options=opt)
+        return SamplerGradientResult(gradients=gradients, metadata=metadata, options=opt)