def getOrAdd(self, config:ATNConfig):
h = config.hashCodeForConfigSet()
l = self.configLookup.get(h, None)
if l is not None:
r = next((cfg for cfg in l if config.equalsForConfigSet(cfg)), None)
if r is not None:
return r
if l is None:
l = [config]
self.configLookup[h] = l
else:
l.append(config)
return config
def getOrAdd(self, config:ATNConfig):
h = config.hashCodeForConfigSet()
l = self.configLookup.get(h, None)
if l is not None:
r = next((cfg for cfg in l if config.equalsForConfigSet(cfg)), None)
if r is not None:
return r
if l is None:
l = [config]
self.configLookup[h] = l
else:
l.append(config)
return config
def getOrAdd(self, config:ATNConfig):
h = config.hashCodeForConfigSet()
l = self.configLookup.get(h, None)
if l is not None:
for c in l:
if config.equalsForConfigSet(c):
return c
if l is None:
l = [config]
self.configLookup[h] = l
else:
l.append(config)
return config
def hasSLLConflictTerminatingPrediction(cls, mode, configs):
# Configs in rule stop states indicate reaching the end of the decision
# rule (local context) or end of start rule (full context). If all
# configs meet this condition, then none of the configurations is able
# to match additional input so we terminate prediction.
#
if cls.allConfigsInRuleStopStates(configs):
return True
# pure SLL mode parsing
if mode == PredictionMode.SLL:
# Don't bother with combining configs from different semantic
# contexts if we can fail over to full LL; costs more time
# since we'll often fail over anyway.
if configs.hasSemanticContext:
# dup configs, tossing out semantic predicates
dup = ATNConfigSet()
for c in configs:
c = ATNConfig(config=c, semantic=SemanticContext.NONE)
dup.add(c)
configs = dup
# now we have combined contexts for configs with dissimilar preds
# pure SLL or combined SLL+LL mode parsing
altsets = cls.getConflictingAltSubsets(configs)
return cls.hasConflictingAltSet(
altsets) and not cls.hasStateAssociatedWithOneAlt(configs)
def _LOOK(self, s, stopState , ctx, look, lookBusy, \
calledRuleStack, seeThruPreds, addEOF):
c = ATNConfig(s, 0, ctx)
if c in lookBusy:
return
lookBusy.add(c)
if s == stopState:
if ctx is None:
look.addOne(Token.EPSILON)
return
elif ctx.isEmpty() and addEOF:
look.addOne(Token.EOF)
return
if isinstance(s, RuleStopState ):
if ctx is None:
look.addOne(Token.EPSILON)
return
elif ctx.isEmpty() and addEOF:
look.addOne(Token.EOF)
return
if ctx != PredictionContext.EMPTY:
# run thru all possible stack tops in ctx
for i in range(0, len(ctx)):
returnState = self.atn.states[ctx.getReturnState(i)]
removed = returnState.ruleIndex in calledRuleStack
try:
calledRuleStack.discard(returnState.ruleIndex)
self._LOOK(returnState, stopState, ctx.getParent(i), look, lookBusy, calledRuleStack, seeThruPreds, addEOF)
finally:
if removed:
calledRuleStack.add(returnState.ruleIndex)
return
for t in s.transitions:
if type(t) == RuleTransition:
if t.target.ruleIndex in calledRuleStack:
continue
newContext = SingletonPredictionContext.create(ctx, t.followState.stateNumber)
try:
calledRuleStack.add(t.target.ruleIndex)
self._LOOK(t.target, stopState, newContext, look, lookBusy, calledRuleStack, seeThruPreds, addEOF)
finally:
calledRuleStack.remove(t.target.ruleIndex)
elif isinstance(t, AbstractPredicateTransition ):
if seeThruPreds:
self._LOOK(t.target, stopState, ctx, look, lookBusy, calledRuleStack, seeThruPreds, addEOF)
else:
look.addOne(self.HIT_PRED)
elif t.isEpsilon:
self._LOOK(t.target, stopState, ctx, look, lookBusy, calledRuleStack, seeThruPreds, addEOF)
elif type(t) == WildcardTransition:
look.addRange( Interval(Token.MIN_USER_TOKEN_TYPE, self.atn.maxTokenType + 1) )
else:
set = t.label
if set is not None:
if isinstance(t, NotSetTransition):
set = set.complement(Token.MIN_USER_TOKEN_TYPE, self.atn.maxTokenType)
look.addSet(set)