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)