class HintBookkeeper(object):
def __init__(self, hannotator):
self.pending_specializations = []
self.originflags = {}
self.virtual_containers = {}
self.descs = {}
self.tsgraph_maximal_call_families = UnionFind(TsGraphCallFamily)
self.annotator = hannotator
self.tsgraphsigs = {}
self.nonstuboriggraphcount = 0
self.stuboriggraphcount = 0
if hannotator is not None: # for tests
t = hannotator.base_translator
self.impurity_analyzer = ImpurityAnalyzer(t)
# circular imports hack
global hintmodel
from pypy.jit.hintannotator import model as hintmodel
def getdesc(self, graph):
try:
return self.descs[graph]
except KeyError:
self.descs[graph] = desc = GraphDesc(self, graph)
return desc
def enter(self, position_key):
"""Start of an operation.
The operation is uniquely identified by the given key."""
res = getattr(self, 'position_key', None)
self.position_key = position_key
TLS.bookkeeper = self
return res
def leave(self, old=None):
"""End of an operation."""
if old is None:
del TLS.bookkeeper
del self.position_key
else:
self.position_key = old
def myinputargorigin(self, graph, i):
try:
origin = self.originflags[graph, i]
except KeyError:
origin = hintmodel.InputArgOriginFlags(self, graph, i)
self.originflags[graph, i] = origin
return origin
def myorigin(self):
try:
origin = self.originflags[self.position_key]
except KeyError:
assert len(self.position_key) == 3
graph, block, i = self.position_key
spaceop = block.operations[i]
spaceop = SpaceOperation(spaceop.opname,
list(spaceop.args),
spaceop.result)
origin = hintmodel.OriginFlags(self, spaceop)
self.originflags[self.position_key] = origin
return origin
def compute_at_fixpoint(self):
binding = self.annotator.binding
# for the entry point, we need to remove the 'myorigin' of
# the input arguments (otherwise they will always be green,
# as there is no call to the entry point to make them red)
tsgraph = self.annotator.translator.graphs[0]
for v in tsgraph.getargs():
hs_arg = binding(v)
if isinstance(hs_arg, hintmodel.SomeLLAbstractConstant):
hs_arg.myorigin = None
# for convenience, force the return var to be red too, as
# the timeshifter doesn't support anything else
if self.annotator.policy.entrypoint_returns_red:
v = tsgraph.getreturnvar()
hs_red = hintmodel.variableoftype(v.concretetype)
self.annotator.setbinding(v, hs_red)
# propagate the green/red constraints
log.event("Computing maximal green set...")
greenorigindependencies = {}
callreturndependencies = {}
for origin in self.originflags.values():
origin.greenargs = True
origin.record_dependencies(greenorigindependencies,
callreturndependencies)
while True:
progress = False
# check all calls to see if they are green calls or not
for origin, graphs in callreturndependencies.items():
if self.is_green_call(origin.spaceop):
pass # green call => don't force spaceop.result to red
else:
# non-green calls: replace the dependency with a regular
# dependency from graph.getreturnvar() to spaceop.result
del callreturndependencies[origin]
retdeps = greenorigindependencies.setdefault(origin, [])
for graph in graphs:
retdeps.append(graph.getreturnvar())
# propagate normal dependencies
for origin, deps in greenorigindependencies.items():
for v in deps:
if not binding(v).is_green():
# not green => force the origin to be red too
origin.greenargs = False
del greenorigindependencies[origin]
progress = True
break
if not progress:
break
for callfamily in self.tsgraph_maximal_call_families.infos():
if len(callfamily.tsgraphs) > 1:
# if at least one graph in the family returns a red,
# we force a red as the return of all of them
returns_red = False
for graph in callfamily.tsgraphs:
if not binding(graph.getreturnvar()).is_green():
returns_red = True
if returns_red:
for graph in callfamily.tsgraphs:
v = graph.getreturnvar()
hs_red = hintmodel.variableoftype(v.concretetype)
self.annotator.setbinding(v, hs_red)
# compute and cache the signature of the graphs before they are
# modified by further code
ha = self.annotator
for tsgraph in ha.translator.graphs:
sig_hs = ([ha.binding(v) for v in tsgraph.getargs()],
ha.binding(tsgraph.getreturnvar()))
self.tsgraphsigs[tsgraph] = sig_hs
def is_pure_graph(self, graph):
impure = self.impurity_analyzer.analyze_direct_call(graph)
return not impure
def is_green_call(self, callop):
"Is the given call operation completely computable at compile-time?"
for v in callop.args:
hs_arg = self.annotator.binding(v)
if not hs_arg.is_green():
return False
# all-green arguments. Note that we can return True even if the
# result appears to be red; it's not a real red result then.
impure = self.impurity_analyzer.analyze(callop)
return not impure
def immutableconstant(self, const):
res = hintmodel.SomeLLAbstractConstant(const.concretetype, {})
res.const = const.value
# we want null pointers to be deepfrozen!
if isinstance(const.concretetype, (lltype.Ptr,
ootype.Instance,
ootype.BuiltinType,
ootype.StaticMethod)):
if not const.value:
res.deepfrozen = True
return res
def immutablevalue(self, value):
return self.immutableconstant(Constant(value, lltype.typeOf(value)))
def current_op_concretetype(self):
_, block, i = self.position_key
op = block.operations[i]
return op.result.concretetype
def current_op_binding(self):
_, block, i = self.position_key
op = block.operations[i]
hs_res = self.annotator.binding(op.result, annmodel.s_ImpossibleValue)
return hs_res
def getvirtualcontainerdef(self, TYPE, constructor=None):
try:
res = self.virtual_containers[self.position_key]
assert res.T == TYPE
except KeyError:
if constructor is None:
from pypy.jit.hintannotator.container import virtualcontainerdef
constructor = virtualcontainerdef
res = constructor(self, TYPE)
self.virtual_containers[self.position_key] = res
return res
def warning(self, msg):
return self.annotator.warning(msg)
def specialization_key(self, fixed, args_hs):
if fixed:
return 'fixed'
else:
key = []
specialize = False
for i, arg_hs in enumerate(args_hs):
if isinstance(arg_hs, hintmodel.SomeLLAbstractVariable):
key.append('v')
specialize = True
continue
if (isinstance(arg_hs, hintmodel.SomeLLAbstractConstant)
and arg_hs.eager_concrete):
key.append('E')
specialize = True
else:
key.append('x')
if (isinstance(arg_hs, hintmodel.SomeLLAbstractConstant)
and arg_hs.deepfrozen):
key.append('D')
specialize = True
else:
key.append('x')
if specialize:
return ''.join(key)
else:
return None
def get_graph_by_key(self, graph, specialization_key):
desc = self.getdesc(graph)
return desc._cache[specialization_key]
def get_graph_for_call(self, graph, fixed, args_hs):
# this can modify args_hs in-place!
key = self.specialization_key(fixed, args_hs)
if key is None:
alt_name = None
else:
alt_name = graph.name + '_H'+key
desc = self.getdesc(graph)
graph = desc.specialize(args_hs, key=key, alt_name=alt_name)
return graph
def graph_call(self, graph, fixed, args_hs,
tsgraph_accum=None, hs_callable=None):
input_args_hs = list(args_hs)
graph = self.get_graph_for_call(graph, fixed, input_args_hs)
if tsgraph_accum is not None:
tsgraph_accum.append(graph) # save this if the caller cares
# propagate fixing of arguments in the function to the caller
for inp_arg_hs, arg_hs in zip(input_args_hs, args_hs):
if isinstance(arg_hs, hintmodel.SomeLLAbstractConstant):
assert len(inp_arg_hs.origins) == 1
[o] = inp_arg_hs.origins.keys()
if o.read_fixed():
for o in arg_hs.origins:
o.set_fixed()
hs_res = self.annotator.recursivecall(graph,
self.position_key,
input_args_hs)
# look on which input args the hs_res result depends on
if isinstance(hs_res, hintmodel.SomeLLAbstractConstant):
if (hs_callable is not None and
not isinstance(hs_callable, hintmodel.SomeLLAbstractConstant)):
hs_res = hintmodel.variableoftype(hs_res.concretetype,
hs_res.deepfrozen)
else:
deps_hs = []
for hs_inputarg, hs_arg in zip(input_args_hs, args_hs):
if isinstance(hs_inputarg,
hintmodel.SomeLLAbstractConstant):
assert len(hs_inputarg.origins) == 1
[o] = hs_inputarg.origins.keys()
if o in hs_res.origins:
deps_hs.append(hs_arg)
if fixed:
deps_hs.append(hs_res)
hs_res = hintmodel.reorigin(hs_res, hs_callable, *deps_hs)
return hs_res
def graph_family_call(self, graph_list, fixed, args_hs,
tsgraphs_accum=None, hs_callable=None):
if tsgraphs_accum is None:
tsgraphs = []
else:
tsgraphs = tsgraphs_accum
results_hs = []
for graph in graph_list:
results_hs.append(self.graph_call(graph, fixed, args_hs,
tsgraphs, hs_callable))
# put the tsgraphs in the same call family
call_families = self.tsgraph_maximal_call_families
_, rep, callfamily = call_families.find(tsgraphs[0])
for tsgraph in tsgraphs[1:]:
_, rep, callfamily = call_families.union(rep, tsgraph)
return annmodel.unionof(*results_hs)
def compute_lifetimes(self, graph):
"""Compute the static data flow of the graph: returns a list of LifeTime
instances, each of which corresponds to a set of Variables from the graph.
The variables are grouped in the same LifeTime if a value can pass from
one to the other by following the links. Each LifeTime also records all
places where a Variable in the set is used (read) or build (created).
"""
lifetimes = UnionFind(LifeTime)
def set_creation_point(block, var, *cp):
_, _, info = lifetimes.find((block, var))
info.creationpoints[cp] = True
def set_use_point(block, var, *up):
_, _, info = lifetimes.find((block, var))
info.usepoints[up] = True
def union(block1, var1, block2, var2):
if isinstance(var1, Variable):
lifetimes.union((block1, var1), (block2, var2))
elif isinstance(var1, Constant):
set_creation_point(block2, var2, "constant", var1)
else:
raise TypeError(var1)
for var in graph.startblock.inputargs:
set_creation_point(graph.startblock, var, "inputargs")
set_use_point(graph.returnblock, graph.returnblock.inputargs[0], "return")
set_use_point(graph.exceptblock, graph.exceptblock.inputargs[0], "except")
set_use_point(graph.exceptblock, graph.exceptblock.inputargs[1], "except")
def visit(node):
if isinstance(node, Block):
for op in node.operations:
if op.opname in self.IDENTITY_OPS:
# special-case these operations to identify their input
# and output variables
union(node, op.args[0], node, op.result)
continue
if op.opname in self.SUBSTRUCT_OPS:
if self.visit_substruct_op(node, union, op):
continue
for i in range(len(op.args)):
if isinstance(op.args[i], Variable):
set_use_point(node, op.args[i], "op", node, op, i)
set_creation_point(node, op.result, "op", node, op)
if isinstance(node.exitswitch, Variable):
set_use_point(node, node.exitswitch, "exitswitch", node)
if isinstance(node, Link):
if isinstance(node.last_exception, Variable):
set_creation_point(node.prevblock, node.last_exception,
"last_exception")
if isinstance(node.last_exc_value, Variable):
set_creation_point(node.prevblock, node.last_exc_value,
"last_exc_value")
d = {}
for i, arg in enumerate(node.args):
union(node.prevblock, arg,
node.target, node.target.inputargs[i])
if isinstance(arg, Variable):
if arg in d:
# same variable present several times in link.args
# consider it as a 'use' of the variable, which
# will disable malloc optimization (aliasing problems)
set_use_point(node.prevblock, arg, "dup", node, i)
else:
d[arg] = True
traverse(visit, graph)
return lifetimes.infos()
def compute_lifetimes(self, graph):
"""Compute the static data flow of the graph: returns a list of LifeTime
instances, each of which corresponds to a set of Variables from the graph.
The variables are grouped in the same LifeTime if a value can pass from
one to the other by following the links. Each LifeTime also records all
places where a Variable in the set is used (read) or build (created).
"""
lifetimes = UnionFind(LifeTime)
def set_creation_point(block, var, *cp):
_, _, info = lifetimes.find((block, var))
info.creationpoints[cp] = True
def set_use_point(block, var, *up):
_, _, info = lifetimes.find((block, var))
info.usepoints[up] = True
def union(block1, var1, block2, var2):
if isinstance(var1, Variable):
lifetimes.union((block1, var1), (block2, var2))
elif isinstance(var1, Constant):
set_creation_point(block2, var2, "constant", var1)
else:
raise TypeError(var1)
for var in graph.startblock.inputargs:
set_creation_point(graph.startblock, var, "inputargs")
set_use_point(graph.returnblock, graph.returnblock.inputargs[0],
"return")
set_use_point(graph.exceptblock, graph.exceptblock.inputargs[0],
"except")
set_use_point(graph.exceptblock, graph.exceptblock.inputargs[1],
"except")
def visit(node):
if isinstance(node, Block):
for op in node.operations:
if op.opname in self.IDENTITY_OPS:
# special-case these operations to identify their input
# and output variables
union(node, op.args[0], node, op.result)
continue
if op.opname in self.SUBSTRUCT_OPS:
if self.visit_substruct_op(node, union, op):
continue
for i in range(len(op.args)):
if isinstance(op.args[i], Variable):
set_use_point(node, op.args[i], "op", node, op, i)
set_creation_point(node, op.result, "op", node, op)
if isinstance(node.exitswitch, Variable):
set_use_point(node, node.exitswitch, "exitswitch", node)
if isinstance(node, Link):
if isinstance(node.last_exception, Variable):
set_creation_point(node.prevblock, node.last_exception,
"last_exception")
if isinstance(node.last_exc_value, Variable):
set_creation_point(node.prevblock, node.last_exc_value,
"last_exc_value")
d = {}
for i, arg in enumerate(node.args):
union(node.prevblock, arg, node.target,
node.target.inputargs[i])
if isinstance(arg, Variable):
if arg in d:
# same variable present several times in link.args
# consider it as a 'use' of the variable, which
# will disable malloc optimization (aliasing problems)
set_use_point(node.prevblock, arg, "dup", node, i)
else:
d[arg] = True
traverse(visit, graph)
return lifetimes.infos()
