Gradient
class Gradient(grad_method='param_shift', **kwargs)
Bases: qiskit.aqua.operators.gradients.gradient_base.GradientBase
Convert an operator expression to the first-order gradient.
Parameters
- grad_method (
Union[str,CircuitGradient]) – 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.
Methods
convert
Gradient.convert(operator, params=None)
Parameters
- operator (
OperatorBase) – The operator we are taking the gradient of. - params (
Union[ParameterVector,ParameterExpression,List[ParameterExpression],None]) – params: The parameters we are taking the gradient with respect to.
Return type
OperatorBase
Returns
An operator whose evaluation yields the Gradient.
Raises
ValueError – If params contains a parameter not present in operator.
get_gradient
Gradient.get_gradient(operator, params)
Get the gradient for the given operator w.r.t. the given parameters
Parameters
- operator (
OperatorBase) – Operator w.r.t. which we take the gradient. - params (
Union[ParameterExpression,ParameterVector,List[ParameterExpression]]) – Parameters w.r.t. which we compute the gradient.
Return type
OperatorBase
Returns
Operator which represents the gradient w.r.t. the given params.
Raises
- ValueError – If
paramscontains a parameter not present inoperator. - AquaError – If the coefficient of the operator could not be reduced to 1.
- AquaError – If the differentiation of a combo_fn requires JAX but the package is not installed.
- TypeError – If the operator does not include a StateFn given by a quantum circuit
- Exception – Unintended code is reached
gradient_wrapper
Gradient.gradient_wrapper(operator, bind_params, grad_params=None, backend=None)
Get a callable function which provides the respective gradient, Hessian or QFI for given parameter values. This callable can be used as gradient function for optimizers.
Parameters
- operator (
OperatorBase) – The operator for which we want to get the gradient, Hessian or QFI. - bind_params (
Union[ParameterExpression,ParameterVector,List[ParameterExpression]]) – The operator parameters to which the parameter values are assigned. - grad_params (
Union[ParameterExpression,ParameterVector,List[ParameterExpression],Tuple[ParameterExpression,ParameterExpression],List[Tuple[ParameterExpression,ParameterExpression]],None]) – The parameters with respect to which we are taking the gradient, Hessian or QFI. If grad_params = None, then grad_params = bind_params - backend (
Union[BaseBackend,QuantumInstance,None]) – The quantum backend or QuantumInstance to use to evaluate the gradient, Hessian or QFI.
Returns
Function to compute a gradient, Hessian or QFI. The function takes an iterable as argument which holds the parameter values.
Return type
callable(param_values)
parameter_expression_grad
static Gradient.parameter_expression_grad(param_expr, param)
Get the derivative of a parameter expression w.r.t. the given parameter.
Parameters
- param_expr (
ParameterExpression) – The Parameter Expression for which we compute the derivative - param (
ParameterExpression) – Parameter w.r.t. which we want to take the derivative
Return type
Union[ParameterExpression, float]
Returns
ParameterExpression representing the gradient of param_expr w.r.t. param
Attributes
grad_method
Returns CircuitGradient.
Return type
CircuitGradient
Returns
CircuitGradient.