/usr/lib/python2.7/dist-packages/vamos/golem/inference.py is in undertaker 1.6-2.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 | """golem - analyzes feature dependencies in Linux makefiles"""
# Copyright (C) 2012 Christian Dietrich <christian.dietrich@informatik.uni-erlangen.de>
# Copyright (C) 2012 Reinhard Tartler <tartler@informatik.uni-erlangen.de>
# Copyright (C) 2014 Stefan Hengelein <stefan.hengelein@fau.de>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
from vamos.selection import Selection
from vamos.tools import get_online_processors
from vamos.golem.FileSet import FileSetCache
from vamos.golem.inference_atoms import *
import logging
import os
import copy
import Queue
import threading
import thread
import time
def objects_in_dir(directory):
""" Returns a tuple of object files and subdirectories in a specific directory """
ret = (set(), set())
for name in os.listdir(directory):
name = os.path.join(directory, name)
# is a directory
if os.path.isdir(name):
ret[1].add(name)
elif name.endswith(".c"):
name = name[:-len(".c")] + ".o"
ret[0].add(name)
return ret
def all_variations(seq_SEQ):
if len(seq_SEQ) == 0:
return [[]]
rest = all_variations(seq_SEQ[1:])
ret = []
for i in seq_SEQ[0]:
for r in rest:
ret.append([i] + r)
return ret
def unique(seq):
# order preserving
noDupes = []
for i in seq:
if not i in noDupes:
noDupes.append(i)
return noDupes
class Counter:
def __init__(self):
self.lock = threading.Lock()
self.int = 0
def inc(self):
with self.lock:
self.int += 1
def dec(self):
with self.lock:
self.int -= 1
def isZero(self):
with self.lock:
return self.int == 0
class Inferencer:
def __init__(self, atoms):
# The atom
self.atoms = atoms
self.cache = FileSetCache(self.atoms)
self.lock = threading.Lock()
self.visited_povs = {}
self.var_impl_selections = {}
self.pov_queue = Queue.Queue()
self.work_queue = Queue.Queue()
self.on_the_run = Counter()
self.running = True
def observer(self):
while not self.on_the_run.isZero():
time.sleep(0.2)
with self.lock:
self.running = False
def work_queue_worker(self):
while self.running:
try:
args = self.work_queue.get(True, 1)
self.__test_selection(*args)
self.on_the_run.dec()
except Queue.Empty:
pass
except Exception as e:
self.running = False
logging.error(str(e))
raise
def generate_variations(self, base_select, pov):
var_ints = self.atoms.OP_features_in_pov(pov)
ret = []
for var_group in var_ints:
group = []
for var_int in var_group:
if type(var_int) == tuple:
group.append([var_int])
else:
values = self.atoms.OP_domain_of_variability_intention(var_int) \
- set([self.atoms.OP_default_value_of_variability_intention(var_int)])
group.append([(var_int, value) for value in values])
base_select_dict = base_select.to_dict()
for variation in all_variations(group):
d = dict(variation)
skip = False
delete_from_var = []
for i in d:
base_select_value = base_select_dict.get(i, None)
if base_select_value != None:
if base_select_value != d[i]:
skip = True
else:
delete_from_var.append(i)
variation = [(var_int, value) for (var_int, value) in variation if not var_int in delete_from_var]
if not skip:
ret.append(variation)
return unique(ret)
def calculate(self):
# pylint: disable=R0912
empty_selection = Selection()
base_var_impl = self.cache.get_fileset(empty_selection)
empty_var_impl = copy.deepcopy(base_var_impl)
empty_var_impl.var_impl = set()
for var_impl in base_var_impl.var_impl:
self.var_impl_selections[var_impl] = [empty_selection]
for pov in empty_var_impl.pov:
self.on_the_run.inc()
self.pov_queue.put(tuple([empty_selection, base_var_impl, pov]))
thread.start_new_thread(self.observer, tuple())
for i in range(0, int(get_online_processors() * 1.5)):
thread.start_new_thread(self.work_queue_worker, tuple())
while self.running:
try:
(base_select, base_var_impl, pov) = self.pov_queue.get(True, 1)
except Queue.Empty:
continue
base_select_is_superset = any([x.better_than(base_select) for x in self.visited_povs.get(pov, [])])
if not base_select_is_superset and self.atoms.pov_worth_working_on(pov):
if not pov in self.visited_povs:
self.visited_povs[pov] = []
self.visited_povs[pov].append(base_select)
logging.info("Visiting POV: %s", pov)
for variation in self.generate_variations(base_select, pov):
new_selection = Selection(base_select)
assert all([not var_int in new_selection.symbols
for (var_int, value) in variation])
for (var_int, value) in variation:
new_selection.push_down()
new_selection.add_alternative(var_int, value)
self.on_the_run.inc()
self.work_queue.put(tuple([pov, new_selection, base_var_impl]))
self.on_the_run.dec()
# Cleanup bad alternatives
for var_impl in self.var_impl_selections:
selection = self.var_impl_selections[var_impl]
i = 0
for i in range(0, len(selection)):
for x in range(0, len(selection)):
if x != i and selection[i] and selection[x] \
and selection[i].better_than(selection[x]):
selection[x] = None
again = True
while again:
again = False
for i in range(0, len(selection)):
for x in range(0, len(selection)):
if x != i and selection[i] and selection[x]:
m = selection[i].merge(selection[x])
if m:
again = True
selection[i] = m
selection[x] = None
self.var_impl_selections[var_impl] = [x for x in selection if x]
for i in self.var_impl_selections:
if len(self.var_impl_selections[i]) > 0:
print '%s "%s"' % (self.atoms.format_var_impl(i),
self.atoms.format_selections(self.var_impl_selections[i]))
else:
print self.atoms.format_var_impl(i)
def __test_selection(self, pov, current_selection, base_var_impl):
new_var_impl = self.cache.get_fileset(current_selection)
((var_impl_added, _), (pov_added, _)) = new_var_impl.compare_to_base(base_var_impl)
with self.lock:
for var_impl in var_impl_added:
if not var_impl in self.var_impl_selections:
self.var_impl_selections[var_impl] = [current_selection]
else:
self.var_impl_selections[var_impl].append(current_selection)
for pov in pov_added:
self.on_the_run.inc()
self.pov_queue.put(tuple([current_selection, new_var_impl, pov]))
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