X-Git-Url: https://gerrit.fd.io/r/gitweb?a=blobdiff_plain;f=resources%2Flibraries%2Fpython%2FMLRsearch%2Fstrategy%2Fbisect.py;fp=resources%2Flibraries%2Fpython%2FMLRsearch%2Fstrategy%2Fbisect.py;h=894544695e1a3eb4926b8540e05f7ceb48d97de2;hb=e5dbe10d9599b9a53fa07e6fadfaf427ba6d69e3;hp=0000000000000000000000000000000000000000;hpb=c6dfb6c09c5dafd1d522f96b4b86c5ec5efc1c83;p=csit.git diff --git a/resources/libraries/python/MLRsearch/strategy/bisect.py b/resources/libraries/python/MLRsearch/strategy/bisect.py new file mode 100644 index 0000000000..894544695e --- /dev/null +++ b/resources/libraries/python/MLRsearch/strategy/bisect.py @@ -0,0 +1,193 @@ +# 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 BisectStrategy class.""" + + +from dataclasses import dataclass +from typing import Optional, Tuple + +from ..discrete_interval import DiscreteInterval +from ..discrete_load import DiscreteLoad +from ..discrete_width import DiscreteWidth +from ..relevant_bounds import RelevantBounds +from .base import StrategyBase + + +@dataclass +class BisectStrategy(StrategyBase): + """Strategy to use when both bounds relevant to curent target are present. + + Primarily, this strategy is there to perform internal search. + As powers of two are fiendly to binary search, + this strategy relies on the splitting logic described in DiscreteInterval. + + The main reason why this class is so long is that a mere existence + of a valid bound for the current target does not imply + that bound is a good approximation of the final conditional throughput. + The bound might become valid due to efforts of a strategy + focusing on an entirely different search goal. + + On the other hand, initial bounds may be better approximations, + but they also may be bad approximations (for example + when SUT behavior strongly depends on trial duration). + + Based on comparison of existing current bounds to intial bounds, + this strategy also mimics what would external search do + (if the one current bound was missing and other initial bound was current). + In case that load value is closer to appropriate inital bound + (compared to how far the simple bisect between current bounds is), + that load is nominated. + + It turns out those "conditional" external search nominations + are quite different from unconditional ones, + at least when it comes to handling limits + and tracking when width expansion should be applied. + That is why that logic is here + and not in some generic external search class. + """ + + expand_on_clo: bool = False + """If extending up, width should be expanded when load becomes clo.""" + expand_on_chi: bool = False + """If extending down, width should be expanded when load becomes chi.""" + + def nominate( + self, bounds: RelevantBounds + ) -> Tuple[Optional[DiscreteLoad], Optional[DiscreteWidth]]: + """Nominate a load candidate between bounds or extending from them. + + The external search logic is offloaded into private methods. + If they return a truthy load, that is returned from here as well. + + Only if the actual bisect is selected, + the per-selector expander is limited to the (smaller) new width. + + :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 bounds.clo or bounds.clo >= self.handler.max_load: + return None, None + if not bounds.chi or bounds.chi <= self.handler.min_load: + return None, None + interval = DiscreteInterval(bounds.clo, bounds.chi) + if interval.width_in_goals(self.target.discrete_width) <= 1.0: + return None, None + bisect_load = interval.middle(self.target.discrete_width) + load, width = self._extend_lo(bounds, bisect_load) + if load: + self.expand_on_clo, self.expand_on_chi = False, True + self.debug(f"Preferring to extend down: {load}") + return load, width + load, width = self._extend_hi(bounds, bisect_load) + if load: + self.expand_on_clo, self.expand_on_chi = True, False + self.debug(f"Preferring to extend up: {load}") + return load, width + load = bisect_load + if self.not_worth(bounds=bounds, load=load): + return None, None + self.expand_on_clo, self.expand_on_chi = False, False + self.debug(f"Preferring to bisect: {load}") + width_lo = DiscreteInterval(bounds.clo, load).discrete_width + width_hi = DiscreteInterval(load, bounds.chi).discrete_width + width = min(width_lo, width_hi) + self.expander.limit(width) + return load, width + + def _extend_lo( + self, bounds: RelevantBounds, bisect_load: DiscreteLoad + ) -> Tuple[Optional[DiscreteLoad], Optional[DiscreteWidth]]: + """Compute load as if extending down, return it if preferred. + + :param bounds: Freshly updated bounds relevant for current target. + :param bisect_load: Load when bisection is preferred. + :type bounds: RelevantBounds + :type bisect_load: DiscreteLoad + :returns: Two nones or candidate intended load and duration. + :rtype: Tuple[Optional[DiscreteLoad], Optional[DiscreteWidth]] + :raises RuntimeError: If an internal inconsistency is detected. + """ + # TODO: Simplify all the conditions or explain them better. + if not self.initial_upper_load: + return None, None + if bisect_load >= self.initial_upper_load: + return None, None + width = self.expander.get_width() + load = bounds.chi - width + load = self.handler.handle( + load=load, + width=self.target.discrete_width, + clo=bounds.clo, + chi=bounds.chi, + ) + if not load: + return None, None + if load <= bisect_load: + return None, None + if load >= self.initial_upper_load: + return None, None + if self.not_worth(bounds=bounds, load=load): + raise RuntimeError(f"Load not worth: {load}") + return load, width + + def _extend_hi( + self, bounds: RelevantBounds, bisect_load: DiscreteLoad + ) -> Tuple[Optional[DiscreteLoad], Optional[DiscreteWidth]]: + """Compute load as if extending up, return it if preferred. + + :param bounds: Freshly updated bounds relevant for current target. + :param bisect_load: Load when bisection is preferred. + :type bounds: RelevantBounds + :type bisect_load: DiscreteLoad + :returns: Two nones or candidate intended load and duration. + :rtype: Tuple[Optional[DiscreteLoad], Optional[DiscreteWidth]] + :raises RuntimeError: If an internal inconsistency is detected. + """ + # TODO: Simplify all the conditions or explain them better. + if not self.initial_lower_load: + return None, None + if bisect_load <= self.initial_lower_load: + return None, None + width = self.expander.get_width() + load = bounds.clo + width + load = self.handler.handle( + load=load, + width=self.target.discrete_width, + clo=bounds.clo, + chi=bounds.chi, + ) + if not load: + return None, None + if load >= bisect_load: + return None, None + if load <= self.initial_lower_load: + return None, None + if self.not_worth(bounds=bounds, load=load): + raise RuntimeError(f"Load not worth: {load}") + return load, width + + def won(self, bounds: RelevantBounds, load: DiscreteLoad) -> None: + """Expand width when appropriate. + + :param bounds: Freshly updated bounds relevant for current target. + :param load: The current load, so strategy does not need to remember. + :type bounds: RelevantBounds + :type load: DiscreteLoad + """ + if self.expand_on_clo and load == bounds.clo: + self.expander.expand() + elif self.expand_on_chi and load == bounds.chi: + self.expander.expand()