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# Copyright (c) 2023 Cisco and/or its affiliates.
# 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.
"""Module defining RefineHiStrategy class."""
from dataclasses import dataclass
from typing import Optional, Tuple
from ..discrete_load import DiscreteLoad
from ..discrete_width import DiscreteWidth
from ..relevant_bounds import RelevantBounds
from .base import StrategyBase
@dataclass
class RefineHiStrategy(StrategyBase):
"""If initial upper bound is still worth it, nominate it.
This usually happens when halving resulted in relevant lower bound,
or if there was no halving (and RefineLoStrategy confirmed initial
lower bound became a relevant lower bound for the new current target).
This either ensures a matching upper bound (target is achieved)
or moves the relevant lower bound higher (triggering external search).
"""
def nominate(
self, bounds: RelevantBounds
) -> Tuple[Optional[DiscreteLoad], Optional[DiscreteWidth]]:
"""Nominate the initial upper bound.
:param bounds: Freshly updated bounds relevant for current target.
:type bounds: RelevantBounds
:returns: Two nones or candidate intended load and duration.
:rtype: Tuple[Optional[DiscreteLoad], Optional[DiscreteWidth]]
"""
if not (load := self.initial_upper_load):
return None, None
if self.not_worth(bounds=bounds, load=load):
return None, None
self.debug(f"Upperbound refinement available: {load}")
# TODO: Limit to possibly smaller than target width?
self.expander.limit(self.target.discrete_width)
return load, self.target.discrete_width
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