Source code for qiskit.opflow.gradients.gradient_base

# This code is part of Qiskit.
# (C) Copyright IBM 2020, 2023.
# 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
# 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.

"""The base interface for Aqua's gradient."""

from typing import Union

from qiskit.utils.deprecation import deprecate_func
from .circuit_gradients.circuit_gradient import CircuitGradient
from .derivative_base import DerivativeBase

[docs]class GradientBase(DerivativeBase): """Deprecated: Base class for first-order operator gradient. Convert an operator expression to the first-order gradient. """ @deprecate_func( since="0.24.0", package_name="qiskit-terra", additional_msg="For code migration guidelines, visit", ) def __init__(self, grad_method: Union[str, CircuitGradient] = "param_shift", **kwargs): r""" Args: grad_method: The method used to compute the state/probability gradient. Can be either ``'param_shift'`` or ``'lin_comb'`` or ``'fin_diff'``. Ignored for gradients w.r.t observable parameters. kwargs (dict): Optional parameters for a CircuitGradient Raises: ValueError: If method != ``fin_diff`` and ``epsilon`` is not None. """ super().__init__() if isinstance(grad_method, CircuitGradient): self._grad_method = grad_method elif grad_method == "param_shift": from .circuit_gradients.param_shift import ParamShift self._grad_method = ParamShift(analytic=True) elif grad_method == "fin_diff": from .circuit_gradients.param_shift import ParamShift epsilon = kwargs.get("epsilon", 1e-6) self._grad_method = ParamShift(analytic=False, epsilon=epsilon) elif grad_method == "lin_comb": from .circuit_gradients.lin_comb import LinComb self._grad_method = LinComb() else: raise ValueError( "Unrecognized input provided for `grad_method`. Please provide" " a CircuitGradient object or one of the pre-defined string" " arguments: {'param_shift', 'fin_diff', 'lin_comb'}. " ) @property def grad_method(self) -> CircuitGradient: """Returns ``CircuitGradient``. Returns: ``CircuitGradient``. """ return self._grad_method