def __init__(self, annotator):
self.annotator = annotator
self.policy = annotator.policy
self.descs = {} # map Python objects to their XxxDesc wrappers
self.methoddescs = {} # map (funcdesc, classdef) to the MethodDesc
self.classdefs = [] # list of all ClassDefs
self.pbctypes = {}
self.seen_mutable = {}
self.listdefs = {} # map position_keys to ListDefs
self.dictdefs = {} # map position_keys to DictDefs
self.immutable_cache = {}
self.classpbc_attr_families = {
} # {'attr': UnionFind(ClassAttrFamily)}
self.frozenpbc_attr_families = UnionFind(description.FrozenAttrFamily)
self.pbc_maximal_call_families = UnionFind(description.CallFamily)
self.emulated_pbc_calls = {}
self.all_specializations = {} # {FuncDesc: specialization-info}
self.pending_specializations = [] # list of callbacks
self.external_class_cache = {} # cache of ExternalType classes
self.needs_generic_instantiate = {}
self.stats = Stats(self)
# used in SomeObject.__new__ for keeping debugging info
self._isomeobject_coming_from = identity_dict()
delayed_imports()
def memo(funcdesc, arglist_s):
from pypy.annotation.model import SomePBC, SomeImpossibleValue, SomeBool
from pypy.annotation.model import unionof
# call the function now, and collect possible results
argvalues = []
for s in arglist_s:
if s.is_constant():
values = [s.const]
elif isinstance(s, SomePBC):
values = []
assert not s.can_be_None, "memo call: cannot mix None and PBCs"
for desc in s.descriptions:
if desc.pyobj is None:
raise Exception(
"memo call with a class or PBC that has no "
"corresponding Python object (%r)" % (desc, ))
values.append(desc.pyobj)
elif isinstance(s, SomeImpossibleValue):
return s # we will probably get more possible args later
elif isinstance(s, SomeBool):
values = [False, True]
else:
raise Exception("memo call: argument must be a class or a frozen "
"PBC, got %r" % (s, ))
argvalues.append(values)
# the list of all possible tuples of arguments to give to the memo function
possiblevalues = cartesian_product(argvalues)
# a MemoTable factory -- one MemoTable per family of arguments that can
# be called together, merged via a UnionFind.
bookkeeper = funcdesc.bookkeeper
try:
memotables = bookkeeper.all_specializations[funcdesc]
except KeyError:
func = funcdesc.pyobj
if func is None:
raise Exception("memo call: no Python function object to call "
"(%r)" % (funcdesc, ))
def compute_one_result(args):
value = func(*args)
memotable = MemoTable(funcdesc, args, value)
memotable.register_finish()
return memotable
memotables = UnionFind(compute_one_result)
bookkeeper.all_specializations[funcdesc] = memotables
# merge the MemoTables for the individual argument combinations
firstvalues = possiblevalues.next()
_, _, memotable = memotables.find(firstvalues)
for values in possiblevalues:
_, _, memotable = memotables.union(firstvalues, values)
if memotable.graph is not None:
return memotable.graph # if already computed
else:
# otherwise, for now, return the union of each possible result
return unionof(
*[bookkeeper.immutablevalue(v) for v in memotable.table.values()])
def get_classpbc_attr_families(self, attrname):
"""Return the UnionFind for the ClassAttrFamilies corresponding to
attributes of the given name.
"""
map = self.classpbc_attr_families
try:
access_sets = map[attrname]
except KeyError:
access_sets = map[attrname] = UnionFind(description.ClassAttrFamily)
return access_sets
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 coalesce_variables(self):
self._unionfind = UnionFind()
pendingblocks = list(self.graph.iterblocks())
while pendingblocks:
block = pendingblocks.pop()
# Aggressively try to coalesce each source variable with its
# target. We start from the end of the graph instead of
# from the beginning. This is a bit arbitrary, but the idea
# is that the end of the graph runs typically more often
# than the start, given that we resume execution from the
# middle during blackholing.
for link in block.exits:
if link.last_exception is not None:
self._depgraph.add_node(link.last_exception)
if link.last_exc_value is not None:
self._depgraph.add_node(link.last_exc_value)
for i, v in enumerate(link.args):
self._try_coalesce(v, link.target.inputargs[i])
def test_cleanup():
state = []
class ReferencedByExternalState(object):
def __init__(self, obj):
state.append(self)
self.obj = obj
def absorb(self, other):
state.remove(other)
uf = UnionFind(ReferencedByExternalState)
uf.find(1)
for i in xrange(1, 10, 2):
uf.union(i, 1)
uf.find(2)
for i in xrange(2, 20, 2):
uf.union(i, 2)
assert len(state) == 2 # we have exactly 2 partitions
def __init__(self, graph):
# Build a list of "unification opportunities": for each block and each
# 'n', an "opportunity" groups the block's nth input variable with
# the nth output variable from each of the incoming links, in a list:
# [Block, blockvar, linkvar, linkvar, linkvar...]
opportunities = []
opportunities_with_const = []
for block, links in mkinsideentrymap(graph).items():
assert links
for n, inputvar in enumerate(block.inputargs):
vars = [block, inputvar]
put_in = opportunities
for link in links:
var = link.args[n]
if not isinstance(var, Variable):
put_in = opportunities_with_const
vars.append(var)
# if any link provides a Constant, record this in
# the opportunities_with_const list instead
put_in.append(vars)
self.opportunities = opportunities
self.opportunities_with_const = opportunities_with_const
self.variable_families = UnionFind()
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()
