# Copyright 2022 IMCL, Department of Computing
# Department of Computing, Hong Kong Polytechnic University
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
from threading import Event
[docs]class Optimizer():
def __init__(self, settings: dict=None):
if settings is not None and not isinstance(settings, dict):
raise ValueError("settings must be either a dictionary or None")
self.settings = settings if settings is not None else {}
self._halt_event = None
[docs] def initialize(self, op_type, halt_event: Event=None):
# store variables
self.op_type = op_type
self._halt_event = halt_event
[docs] def optimize(self):
raise NotImplementedError
[docs] def get_result(self):
raise NotImplementedError
[docs] def get_cost(self):
raise NotImplementedError