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108 lines
3.3 KiB
108 lines
3.3 KiB
# Copyright (c) 2013 The Chromium OS Authors. All rights reserved.
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# Use of this source code is governed by a BSD-style license that can be
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# found in the LICENSE file.
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"""A variation of the hill climbing algorithm.
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Part of the Chrome build flags optimization.
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This algorithm explores all the neighbors of the current task. If at least one
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neighbor gives better performance than the current task, it explores the best
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neighbor.
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"""
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__author__ = 'yuhenglong@google.com (Yuheng Long)'
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from flags import FlagSet
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import flags_util
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from generation import Generation
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from task import Task
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class HillClimbingBestBranch(Generation):
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"""A variation of the hill climbing algorithm.
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Given a task, it explores all its neighbors. Pick the best neighbor for the
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next iteration.
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"""
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def __init__(self, exe_set, parents, specs):
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"""Set up the tasks set of this generation.
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Args:
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exe_set: A set of tasks to be run.
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parents: A set of tasks to be used to check whether their neighbors have
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improved upon them.
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specs: A list of specs to explore. The spec specifies the flags that can
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be changed to find neighbors of a task.
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"""
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Generation.__init__(self, exe_set, parents)
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self._specs = specs
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# This variable will be used, by the Next method, to generate the tasks for
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# the next iteration. This self._next_task contains the best task in the
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# current iteration and it will be set by the IsImproved method. The tasks
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# of the next iteration are the neighbor of self._next_task.
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self._next_task = None
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def IsImproved(self):
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"""True if this generation has improvement over its parent generation.
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If this generation improves upon the previous generation, this method finds
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out the best task in this generation and sets it to _next_task for the
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method Next to use.
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Returns:
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True if the best neighbor improves upon the parent task.
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"""
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# Find the best neighbor.
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best_task = None
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for task in self._exe_set:
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if not best_task or task.IsImproved(best_task):
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best_task = task
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if not best_task:
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return False
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# The first generation may not have parent generation.
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parents = list(self._candidate_pool)
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if parents:
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assert len(parents) == 1
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self._next_task = best_task
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# If the best neighbor improves upon the parent task.
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return best_task.IsImproved(parents[0])
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self._next_task = best_task
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return True
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def Next(self, cache):
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"""Calculate the next generation.
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The best neighbor b of the current task is the parent of the next
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generation. The neighbors of b will be the set of tasks to be evaluated
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next.
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Args:
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cache: A set of tasks that have been generated before.
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Returns:
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A set of new generations.
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"""
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# The best neighbor.
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current_task = self._next_task
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flag_set = current_task.GetFlags()
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# The neighbors of the best neighbor.
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children_tasks = set([])
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for spec in self._specs:
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for next_flag in flags_util.ClimbNext(flag_set.GetFlags(), spec):
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new_task = Task(FlagSet(next_flag.values()))
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if new_task not in cache:
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children_tasks.add(new_task)
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return [HillClimbingBestBranch(children_tasks, set([current_task]),
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self._specs)]
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