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提交 4cbd9ff5 authored 作者: Frederic's avatar Frederic
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Better interface for cleanup opt

上级 54482de9
隐藏空白字符变更
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正在显示 包含 90 行增加 和 44 行删除
theano/compile/mode.py
浏览文件 @ 4cbd9ff5
......@@ -200,6 +200,12 @@ optdb.register('merge1', gof.MergeOptimizer(),
# rearranges elemwise expressions
optdb.register('canonicalize', gof.EquilibriumDB(ignore_newtrees=False),
1, 'fast_run', 'fast_compile')
# Register in the canonizer Equilibrium as a local opt the merge opt.
# Without this, as the equilibrium have ignore_newtrees=False, we
# won't merge all nodes if it is set as a global optimizer with
# final_opt=True.
optdb['canonicalize'].register("merge", gof.opt.merge_optimizer, 'fast_run',
"fast_compile", cleanup=True)
optdb.register('merge1.2', gof.MergeOptimizer(),
1.2, 'fast_run', 'fast_compile', 'merge')
......
theano/gof/opt.py
浏览文件 @ 4cbd9ff5
......@@ -1774,8 +1774,6 @@ class NavigatorOptimizer(Optimizer):
raise
if replacements is False or replacements is None:
return False
if replacements is True:
return True
old_vars = node.outputs
if isinstance(replacements, dict):
old_vars = list(replacements.keys())
......@@ -1998,7 +1996,8 @@ class EquilibriumOptimizer(NavigatorOptimizer):
failure_callback=None,
ignore_newtrees=True,
max_use_ratio=None,
final_optimizers=None):
final_optimizers=None,
cleanup_optimizers=None):
super(EquilibriumOptimizer, self).__init__(
None,
ignore_newtrees=ignore_newtrees,
......@@ -2007,6 +2006,7 @@ class EquilibriumOptimizer(NavigatorOptimizer):
self.local_optimizers_all = []
self.global_optimizers = []
self.final_optimizers = []
self.cleanup_optimizers = []
for opt in optimizers:
if isinstance(opt, LocalOptimizer):
......@@ -2019,6 +2019,8 @@ class EquilibriumOptimizer(NavigatorOptimizer):
self.global_optimizers.append(opt)
if final_optimizers:
self.final_optimizers = final_optimizers
if cleanup_optimizers:
self.cleanup_optimizers = cleanup_optimizers
self.max_use_ratio = max_use_ratio
assert self.max_use_ratio is not None, (
'max_use_ratio has to be a number')
......@@ -2042,6 +2044,8 @@ class EquilibriumOptimizer(NavigatorOptimizer):
opt.add_requirements(fgraph)
for opt in self.final_optimizers:
opt.add_requirements(fgraph)
for opt in self.cleanup_optimizers:
opt.add_requirements(fgraph)
def apply(self, fgraph, start_from=None):
change_tracker = ChangeTracker()
......@@ -2069,9 +2073,11 @@ class EquilibriumOptimizer(NavigatorOptimizer):
node_created = {}
global_sub_profs = []
final_sub_profs = []
cleanup_sub_profs = []
for opt in (self.global_optimizers +
list(self.get_local_optimizers()) +
self.final_optimizers):
self.final_optimizers +
self.cleanup_optimizers):
global_process_count.setdefault(opt, 0)
time_opts.setdefault(opt, 0)
node_created.setdefault(opt, 0)
......@@ -2080,7 +2086,7 @@ class EquilibriumOptimizer(NavigatorOptimizer):
process_count = {}
t0 = time.time()
changed = False
iter_cleanup_sub_profs = {}
# apply global optimizers
sub_profs = []
for gopt in self.global_optimizers:
......@@ -2104,6 +2110,17 @@ class EquilibriumOptimizer(NavigatorOptimizer):
global_opt_timing.append(float(time.time() - t0))
# apply clean up as global opt can have done changes that
# request that
for copt in self.cleanup_optimizers:
change_tracker.reset()
t_opt = time.time()
sub_prof = copt.apply(fgraph)
time_opts[copt] += time.time() - t_opt
iter_cleanup_sub_profs[copt] = [sub_prof]
if change_tracker.changed:
changed = True
# apply local optimizer
topo_t0 = time.time()
q = deque(graph.io_toposort(fgraph.inputs, start_from))
......@@ -2137,12 +2154,18 @@ class EquilibriumOptimizer(NavigatorOptimizer):
t_opt = time.time()
lopt_change = self.process_node(fgraph, node, lopt)
time_opts[lopt] += time.time() - t_opt
# TODO: if not ...: continue
if lopt_change:
process_count.setdefault(lopt, 0)
process_count[lopt] += 1
global_process_count[lopt] += 1
changed = True
node_created[lopt] += change_tracker.nb_imported - nb
for copt in self.cleanup_optimizers:
t_opt = time.time()
sub_prof = copt.apply(fgraph)
time_opts[copt] += time.time() - t_opt
iter_cleanup_sub_profs[copt].append(sub_prof)
if global_process_count[lopt] > max_use:
max_use_abort = True
opt_name = (getattr(lopt, "name", None) or
......@@ -2176,7 +2199,23 @@ class EquilibriumOptimizer(NavigatorOptimizer):
final_sub_profs.append(sub_profs)
global_opt_timing[-1] += time.time() - t_before_final_opt
# apply clean up as final opt can have done changes that
# request that
for copt in self.cleanup_optimizers:
t_opt = time.time()
sub_prof = copt.apply(fgraph)
time_opts[copt] += time.time() - t_opt
iter_cleanup_sub_profs[copt] = [sub_prof]
# merge clean up profiles during that iteration.
c_sub_profs = []
for copt, sub_profs in iteritems(iter_cleanup_sub_profs):
sub_prof = sub_profs[0]
for s_p in sub_profs[1:]:
sub_prof = copt.merge_profile(sub_prof, s_p)
c_sub_profs.append(sub_prof)
cleanup_sub_profs.append(c_sub_profs)
loop_process_count.append(process_count)
loop_timing.append(float(time.time() - t0))
......@@ -2191,7 +2230,7 @@ class EquilibriumOptimizer(NavigatorOptimizer):
return (self, loop_timing, loop_process_count,
(start_nb_nodes, end_nb_nodes, max_nb_nodes),
global_opt_timing, nb_nodes, time_opts, io_toposort_timing,
node_created, global_sub_profs, final_sub_profs)
node_created, global_sub_profs, final_sub_profs, cleanup_sub_profs)
def print_summary(self, stream=sys.stdout, level=0, depth=-1):
name = getattr(self, 'name', None)
......@@ -2207,7 +2246,8 @@ class EquilibriumOptimizer(NavigatorOptimizer):
(opt, loop_timing, loop_process_count,
(start_nb_nodes, end_nb_nodes, max_nb_nodes),
global_opt_timing, nb_nodes, time_opts, io_toposort_timing,
node_created, global_sub_profs, final_sub_profs) = prof
node_created, global_sub_profs, final_sub_profs,
cleanup_sub_profs) = prof
blanc = (' ' * level)
print(blanc, "EquilibriumOptimizer", end=' ', file=stream)
......@@ -2225,6 +2265,8 @@ class EquilibriumOptimizer(NavigatorOptimizer):
print(blanc, " time in global optimizers %.3fs" % s, file=stream)
s = sum([time_opts[o] for o in opt.final_optimizers])
print(blanc, " time in final optimizers %.3fs" % s, file=stream)
s = sum([time_opts[o] for o in opt.cleanup_optimizers])
print(blanc, " time in cleanup optimizers %.3fs" % s, file=stream)
for i in range(len(loop_timing)):
lopt = ""
if loop_process_count[i]:
......@@ -2248,7 +2290,8 @@ class EquilibriumOptimizer(NavigatorOptimizer):
process_count = {}
for o in (opt.global_optimizers +
list(opt.get_local_optimizers()) +
list(opt.final_optimizers)):
list(opt.final_optimizers) +
list(opt.cleanup_optimizers)):
process_count.setdefault(o, 0)
for count in loop_process_count:
for o, v in iteritems(count):
......@@ -2278,12 +2321,13 @@ class EquilibriumOptimizer(NavigatorOptimizer):
print(blanc + " ", ' %.3fs - %s' % (t, o), file=stream)
print(file=stream)
gf_opts = [o for o in (opt.global_optimizers +
list(opt.final_optimizers))
list(opt.final_optimizers) +
list(opt.cleanup_optimizers))
if o.print_profile.func_code is not
Optimizer.print_profile.func_code]
if not gf_opts:
return
print(blanc, "Global and final optimizer", file=stream)
print(blanc, "Global, final and clean up optimizers", file=stream)
for i in range(len(loop_timing)):
print(blanc, "Iter %d" % i, file=stream)
for o, prof in zip(opt.global_optimizers, global_sub_profs[i]):
......@@ -2296,6 +2340,11 @@ class EquilibriumOptimizer(NavigatorOptimizer):
o.print_profile(stream, prof, level + 2)
except NotImplementedError:
print(blanc, "merge not implemented for ", o)
for o, prof in zip(opt.cleanup_optimizers, cleanup_sub_profs[i]):
try:
o.print_profile(stream, prof, level + 2)
except NotImplementedError:
print(blanc, "merge not implemented for ", o)
@staticmethod
def merge_profile(prof1, prof2):
......@@ -2310,10 +2359,16 @@ class EquilibriumOptimizer(NavigatorOptimizer):
prof2[0].final_optimizers)
else:
final_optimizers = None
if len(prof1[0].cleanup_optimizers) > 0 or len(prof2[0].cleanup_optimizers) > 0:
cleanup_optimizers = OrderedSet(prof1[0].cleanup_optimizers).union(
prof2[0].cleanup_optimizers)
else:
cleanup_optimizers = None
new_opt = EquilibriumOptimizer(
local_optimizers.union(global_optimizers),
max_use_ratio=1,
final_optimizers=final_optimizers)
final_optimizers=final_optimizers,
cleanup_optimizers=cleanup_optimizers)
def merge_list(l1, l2):
l = copy.copy(l1)
......@@ -2361,6 +2416,7 @@ class EquilibriumOptimizer(NavigatorOptimizer):
node_created = merge_dict(prof1[8], prof2[8])
global_sub_profs = merge_list(prof1[9], prof2[9])
final_sub_profs = merge_list(prof1[10], prof2[10])
cleanup_sub_profs = merge_list(prof1[10], prof2[10])
return (new_opt,
loop_timing,
loop_process_count,
......@@ -2371,7 +2427,8 @@ class EquilibriumOptimizer(NavigatorOptimizer):
io_toposort_timing,
node_created,
global_sub_profs,
final_sub_profs)
final_sub_profs,
cleanup_sub_profs)
#################
# Utilities #
......
theano/gof/optdb.py
浏览文件 @ 4cbd9ff5
......@@ -265,28 +265,35 @@ class EquilibriumDB(DB):
super(EquilibriumDB, self).__init__()
self.ignore_newtrees = ignore_newtrees
self.__final__ = {}
self.__cleanup__ = {}
def register(self, name, obj, *tags, **kwtags):
if 'final_opt' in kwtags:
final_opt = kwtags['final_opt']
kwtags.pop('final_opt', None)
else:
final_opt = False
final_opt = kwtags.pop('final_opt', False)
cleanup = kwtags.pop('cleanup', False)
# An opt should not be final and clean up
assert not (final_opt and cleanup)
super(EquilibriumDB, self).register(name, obj, *tags, **kwtags)
self.__final__[name] = final_opt
self.__cleanup__[name] = cleanup
def query(self, *tags, **kwtags):
_opts = super(EquilibriumDB, self).query(*tags, **kwtags)
final_opts = [o for o in _opts if self.__final__.get(o.name, False)]
opts = [o for o in _opts if o not in final_opts]
cleanup_opts = [o for o in _opts if self.__cleanup__.get(o.name,
False)]
opts = [o for o in _opts
if o not in final_opts and o not in cleanup_opts]
if len(final_opts) == 0:
final_opts = None
if len(cleanup_opts) == 0:
cleanup_opts = None
return opt.EquilibriumOptimizer(
opts,
max_use_ratio=config.optdb.max_use_ratio,
ignore_newtrees=self.ignore_newtrees,
failure_callback=opt.NavigatorOptimizer.warn_inplace,
final_optimizers=final_opts)
final_optimizers=final_opts,
cleanup_optimizers=cleanup_opts)
class SequenceDB(DB):
......
theano/tensor/opt.py
浏览文件 @ 4cbd9ff5
......@@ -47,7 +47,6 @@ from theano.tensor.type import (values_eq_approx_remove_inf,
from theano.gof.opt import (Optimizer, pre_constant_merge,
pre_greedy_local_optimizer)
from theano.gof.opt import merge_optimizer
from theano.gof import toolbox
from theano.tensor.basic import get_scalar_constant_value, ShapeError, NotScalarConstantError
from six import StringIO
......@@ -504,29 +503,6 @@ def register_specialize_device(lopt, *tags, **kwargs):
return lopt
# Register in the canonizer Equilibrium as a local opt the merge opt.
# Without this, as the equilibrium have ignore_newtrees=False, we
# won't merge all nodes if it is set as a global optimizer with
# final_opt=True.
#
# This work due to those properties:
# 1) the EQ will execute first the optimizer that trac all nodes.
# 2) after an local optimization being applied, if the
# current node is still in the graph, it will continue to the next
# local optimizer. So this won't trigger more iteration.
def add_merge_feature(fgraph):
if not hasattr(fgraph, 'merge_feature'):
fgraph.attach_feature(theano.gof.opt.MergeFeature())
@register_canonicalize('fast_compile', 'merge')
@gof.local_optimizer(None, requirements=[add_merge_feature])
def local_merge_optimizer(node):
if node.fgraph.merge_feature.scheduled:
ret = merge_optimizer(node.fgraph)
return ret[5] > 0
#####################
# Dot optimizations #
#####################
......
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