Source code for qilisdk.optimizers.optimizer

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from abc import ABC, abstractmethod
from typing import Callable

from .optimizer_result import OptimizerResult


[docs] class Optimizer(ABC): @abstractmethod
[docs] def optimize( self, cost_function: Callable[[list[float]], float], init_parameters: list[float], bounds: list[tuple[float, float]], store_intermediate_results: bool = False, ) -> OptimizerResult: """optimize the cost function and return the optimal parameters. Args: cost_function (Callable[[list[float]], float]): a function that takes in a list of parameters and returns the cost. init_parameters (list[float]): the list of initial parameters. Note: the length of this list determines the number of parameters the optimizer will consider. bounds (list[float, float]): a list of the variable value bounds. Returns: list[float]: the optimal set of parameters that minimize the cost function. """