624 lines
22 KiB
Python
624 lines
22 KiB
Python
#
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# Copyright (c) 2012-2017 The ANTLR Project. All rights reserved.
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# Use of this file is governed by the BSD 3-clause license that
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# can be found in the LICENSE.txt file in the project root.
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#/
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from io import StringIO
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from antlr4.error.Errors import IllegalStateException
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from antlr4.RuleContext import RuleContext
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from antlr4.atn.ATN import ATN
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from antlr4.atn.ATNState import ATNState
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class PredictionContext(object):
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# Represents {@code $} in local context prediction, which means wildcard.
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# {@code#+x =#}.
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#/
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EMPTY = None
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# Represents {@code $} in an array in full context mode, when {@code $}
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# doesn't mean wildcard: {@code $ + x = [$,x]}. Here,
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# {@code $} = {@link #EMPTY_RETURN_STATE}.
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#/
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EMPTY_RETURN_STATE = 0x7FFFFFFF
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globalNodeCount = 1
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id = globalNodeCount
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# Stores the computed hash code of this {@link PredictionContext}. The hash
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# code is computed in parts to match the following reference algorithm.
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#
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# <pre>
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# private int referenceHashCode() {
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# int hash = {@link MurmurHash#initialize MurmurHash.initialize}({@link #INITIAL_HASH});
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#
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# for (int i = 0; i < {@link #size()}; i++) {
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# hash = {@link MurmurHash#update MurmurHash.update}(hash, {@link #getParent getParent}(i));
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# }
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#
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# for (int i = 0; i < {@link #size()}; i++) {
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# hash = {@link MurmurHash#update MurmurHash.update}(hash, {@link #getReturnState getReturnState}(i));
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# }
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#
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# hash = {@link MurmurHash#finish MurmurHash.finish}(hash, 2# {@link #size()});
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# return hash;
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# }
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# </pre>
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#/
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def __init__(self, cachedHashCode:int):
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self.cachedHashCode = cachedHashCode
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def __len__(self):
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return 0
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# This means only the {@link #EMPTY} context is in set.
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def isEmpty(self):
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return self is self.EMPTY
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def hasEmptyPath(self):
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return self.getReturnState(len(self) - 1) == self.EMPTY_RETURN_STATE
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def getReturnState(self, index:int):
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raise IllegalStateException("illegal!")
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def __hash__(self):
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return self.cachedHashCode
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def calculateHashCode(parent:PredictionContext, returnState:int):
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return hash("") if parent is None else hash((hash(parent), returnState))
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def calculateListsHashCode(parents:[], returnStates:[] ):
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h = 0
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for parent, returnState in zip(parents, returnStates):
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h = hash((h, calculateHashCode(parent, returnState)))
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return h
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# Used to cache {@link PredictionContext} objects. Its used for the shared
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# context cash associated with contexts in DFA states. This cache
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# can be used for both lexers and parsers.
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class PredictionContextCache(object):
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def __init__(self):
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self.cache = dict()
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# Add a context to the cache and return it. If the context already exists,
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# return that one instead and do not add a new context to the cache.
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# Protect shared cache from unsafe thread access.
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#
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def add(self, ctx:PredictionContext):
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if ctx==PredictionContext.EMPTY:
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return PredictionContext.EMPTY
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existing = self.cache.get(ctx, None)
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if existing is not None:
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return existing
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self.cache[ctx] = ctx
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return ctx
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def get(self, ctx:PredictionContext):
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return self.cache.get(ctx, None)
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def __len__(self):
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return len(self.cache)
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class SingletonPredictionContext(PredictionContext):
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@staticmethod
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def create(parent:PredictionContext , returnState:int ):
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if returnState == PredictionContext.EMPTY_RETURN_STATE and parent is None:
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# someone can pass in the bits of an array ctx that mean $
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return SingletonPredictionContext.EMPTY
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else:
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return SingletonPredictionContext(parent, returnState)
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def __init__(self, parent:PredictionContext, returnState:int):
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hashCode = calculateHashCode(parent, returnState)
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super().__init__(hashCode)
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self.parentCtx = parent
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self.returnState = returnState
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def __len__(self):
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return 1
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def getParent(self, index:int):
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return self.parentCtx
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def getReturnState(self, index:int):
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return self.returnState
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def __eq__(self, other):
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if self is other:
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return True
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elif other is None:
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return False
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elif not isinstance(other, SingletonPredictionContext):
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return False
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else:
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return self.returnState == other.returnState and self.parentCtx == other.parentCtx
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def __hash__(self):
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return self.cachedHashCode
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def __str__(self):
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up = "" if self.parentCtx is None else str(self.parentCtx)
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if len(up)==0:
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if self.returnState == self.EMPTY_RETURN_STATE:
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return "$"
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else:
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return str(self.returnState)
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else:
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return str(self.returnState) + " " + up
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class EmptyPredictionContext(SingletonPredictionContext):
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def __init__(self):
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super().__init__(None, self.EMPTY_RETURN_STATE)
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def isEmpty(self):
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return True
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def __eq__(self, other):
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return self is other
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def __hash__(self):
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return self.cachedHashCode
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def __str__(self):
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return "$"
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PredictionContext.EMPTY = EmptyPredictionContext()
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class ArrayPredictionContext(PredictionContext):
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# Parent can be null only if full ctx mode and we make an array
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# from {@link #EMPTY} and non-empty. We merge {@link #EMPTY} by using null parent and
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# returnState == {@link #EMPTY_RETURN_STATE}.
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def __init__(self, parents:list, returnStates:list):
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super().__init__(calculateListsHashCode(parents, returnStates))
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self.parents = parents
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self.returnStates = returnStates
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def isEmpty(self):
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# since EMPTY_RETURN_STATE can only appear in the last position, we
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# don't need to verify that size==1
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return self.returnStates[0]==PredictionContext.EMPTY_RETURN_STATE
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def __len__(self):
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return len(self.returnStates)
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def getParent(self, index:int):
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return self.parents[index]
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def getReturnState(self, index:int):
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return self.returnStates[index]
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def __eq__(self, other):
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if self is other:
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return True
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elif not isinstance(other, ArrayPredictionContext):
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return False
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elif hash(self) != hash(other):
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return False # can't be same if hash is different
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else:
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return self.returnStates==other.returnStates and self.parents==other.parents
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def __str__(self):
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if self.isEmpty():
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return "[]"
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with StringIO() as buf:
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buf.write("[")
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for i in range(0,len(self.returnStates)):
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if i>0:
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buf.write(", ")
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if self.returnStates[i]==PredictionContext.EMPTY_RETURN_STATE:
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buf.write("$")
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continue
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buf.write(str(self.returnStates[i]))
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if self.parents[i] is not None:
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buf.write(' ')
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buf.write(str(self.parents[i]))
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else:
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buf.write("null")
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buf.write("]")
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return buf.getvalue()
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def __hash__(self):
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return self.cachedHashCode
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# Convert a {@link RuleContext} tree to a {@link PredictionContext} graph.
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# Return {@link #EMPTY} if {@code outerContext} is empty or null.
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#/
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def PredictionContextFromRuleContext(atn:ATN, outerContext:RuleContext=None):
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if outerContext is None:
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outerContext = RuleContext.EMPTY
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# if we are in RuleContext of start rule, s, then PredictionContext
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# is EMPTY. Nobody called us. (if we are empty, return empty)
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if outerContext.parentCtx is None or outerContext is RuleContext.EMPTY:
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return PredictionContext.EMPTY
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# If we have a parent, convert it to a PredictionContext graph
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parent = PredictionContextFromRuleContext(atn, outerContext.parentCtx)
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state = atn.states[outerContext.invokingState]
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transition = state.transitions[0]
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return SingletonPredictionContext.create(parent, transition.followState.stateNumber)
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def merge(a:PredictionContext, b:PredictionContext, rootIsWildcard:bool, mergeCache:dict):
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# share same graph if both same
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if a==b:
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return a
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if isinstance(a, SingletonPredictionContext) and isinstance(b, SingletonPredictionContext):
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return mergeSingletons(a, b, rootIsWildcard, mergeCache)
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# At least one of a or b is array
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# If one is $ and rootIsWildcard, return $ as# wildcard
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if rootIsWildcard:
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if isinstance( a, EmptyPredictionContext ):
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return a
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if isinstance( b, EmptyPredictionContext ):
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return b
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# convert singleton so both are arrays to normalize
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if isinstance( a, SingletonPredictionContext ):
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a = ArrayPredictionContext([a.parentCtx], [a.returnState])
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if isinstance( b, SingletonPredictionContext):
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b = ArrayPredictionContext([b.parentCtx], [b.returnState])
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return mergeArrays(a, b, rootIsWildcard, mergeCache)
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#
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# Merge two {@link SingletonPredictionContext} instances.
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#
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# <p>Stack tops equal, parents merge is same; return left graph.<br>
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# <embed src="images/SingletonMerge_SameRootSamePar.svg" type="image/svg+xml"/></p>
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#
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# <p>Same stack top, parents differ; merge parents giving array node, then
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# remainders of those graphs. A new root node is created to point to the
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# merged parents.<br>
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# <embed src="images/SingletonMerge_SameRootDiffPar.svg" type="image/svg+xml"/></p>
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#
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# <p>Different stack tops pointing to same parent. Make array node for the
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# root where both element in the root point to the same (original)
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# parent.<br>
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# <embed src="images/SingletonMerge_DiffRootSamePar.svg" type="image/svg+xml"/></p>
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#
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# <p>Different stack tops pointing to different parents. Make array node for
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# the root where each element points to the corresponding original
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# parent.<br>
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# <embed src="images/SingletonMerge_DiffRootDiffPar.svg" type="image/svg+xml"/></p>
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#
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# @param a the first {@link SingletonPredictionContext}
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# @param b the second {@link SingletonPredictionContext}
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# @param rootIsWildcard {@code true} if this is a local-context merge,
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# otherwise false to indicate a full-context merge
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# @param mergeCache
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#/
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def mergeSingletons(a:SingletonPredictionContext, b:SingletonPredictionContext, rootIsWildcard:bool, mergeCache:dict):
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if mergeCache is not None:
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previous = mergeCache.get((a,b), None)
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if previous is not None:
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return previous
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previous = mergeCache.get((b,a), None)
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if previous is not None:
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return previous
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merged = mergeRoot(a, b, rootIsWildcard)
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if merged is not None:
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if mergeCache is not None:
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mergeCache[(a, b)] = merged
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return merged
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if a.returnState==b.returnState:
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parent = merge(a.parentCtx, b.parentCtx, rootIsWildcard, mergeCache)
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# if parent is same as existing a or b parent or reduced to a parent, return it
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if parent == a.parentCtx:
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return a # ax + bx = ax, if a=b
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if parent == b.parentCtx:
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return b # ax + bx = bx, if a=b
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# else: ax + ay = a'[x,y]
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# merge parents x and y, giving array node with x,y then remainders
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# of those graphs. dup a, a' points at merged array
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# new joined parent so create new singleton pointing to it, a'
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merged = SingletonPredictionContext.create(parent, a.returnState)
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if mergeCache is not None:
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mergeCache[(a, b)] = merged
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return merged
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else: # a != b payloads differ
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# see if we can collapse parents due to $+x parents if local ctx
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singleParent = None
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if a is b or (a.parentCtx is not None and a.parentCtx==b.parentCtx): # ax + bx = [a,b]x
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singleParent = a.parentCtx
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if singleParent is not None: # parents are same
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# sort payloads and use same parent
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payloads = [ a.returnState, b.returnState ]
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if a.returnState > b.returnState:
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payloads = [ b.returnState, a.returnState ]
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parents = [singleParent, singleParent]
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merged = ArrayPredictionContext(parents, payloads)
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if mergeCache is not None:
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mergeCache[(a, b)] = merged
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return merged
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# parents differ and can't merge them. Just pack together
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# into array; can't merge.
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# ax + by = [ax,by]
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payloads = [ a.returnState, b.returnState ]
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parents = [ a.parentCtx, b.parentCtx ]
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if a.returnState > b.returnState: # sort by payload
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payloads = [ b.returnState, a.returnState ]
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parents = [ b.parentCtx, a.parentCtx ]
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merged = ArrayPredictionContext(parents, payloads)
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if mergeCache is not None:
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mergeCache[(a, b)] = merged
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return merged
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#
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# Handle case where at least one of {@code a} or {@code b} is
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# {@link #EMPTY}. In the following diagrams, the symbol {@code $} is used
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# to represent {@link #EMPTY}.
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#
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# <h2>Local-Context Merges</h2>
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#
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# <p>These local-context merge operations are used when {@code rootIsWildcard}
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# is true.</p>
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#
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# <p>{@link #EMPTY} is superset of any graph; return {@link #EMPTY}.<br>
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# <embed src="images/LocalMerge_EmptyRoot.svg" type="image/svg+xml"/></p>
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#
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# <p>{@link #EMPTY} and anything is {@code #EMPTY}, so merged parent is
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# {@code #EMPTY}; return left graph.<br>
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# <embed src="images/LocalMerge_EmptyParent.svg" type="image/svg+xml"/></p>
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#
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# <p>Special case of last merge if local context.<br>
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# <embed src="images/LocalMerge_DiffRoots.svg" type="image/svg+xml"/></p>
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#
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# <h2>Full-Context Merges</h2>
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#
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# <p>These full-context merge operations are used when {@code rootIsWildcard}
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# is false.</p>
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#
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# <p><embed src="images/FullMerge_EmptyRoots.svg" type="image/svg+xml"/></p>
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#
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# <p>Must keep all contexts; {@link #EMPTY} in array is a special value (and
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# null parent).<br>
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# <embed src="images/FullMerge_EmptyRoot.svg" type="image/svg+xml"/></p>
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#
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# <p><embed src="images/FullMerge_SameRoot.svg" type="image/svg+xml"/></p>
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#
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# @param a the first {@link SingletonPredictionContext}
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# @param b the second {@link SingletonPredictionContext}
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# @param rootIsWildcard {@code true} if this is a local-context merge,
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# otherwise false to indicate a full-context merge
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#/
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def mergeRoot(a:SingletonPredictionContext, b:SingletonPredictionContext, rootIsWildcard:bool):
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if rootIsWildcard:
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if a == PredictionContext.EMPTY:
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return PredictionContext.EMPTY ## + b =#
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if b == PredictionContext.EMPTY:
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return PredictionContext.EMPTY # a +# =#
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else:
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if a == PredictionContext.EMPTY and b == PredictionContext.EMPTY:
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return PredictionContext.EMPTY # $ + $ = $
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elif a == PredictionContext.EMPTY: # $ + x = [$,x]
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payloads = [ b.returnState, PredictionContext.EMPTY_RETURN_STATE ]
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parents = [ b.parentCtx, None ]
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return ArrayPredictionContext(parents, payloads)
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elif b == PredictionContext.EMPTY: # x + $ = [$,x] ($ is always first if present)
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payloads = [ a.returnState, PredictionContext.EMPTY_RETURN_STATE ]
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parents = [ a.parentCtx, None ]
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return ArrayPredictionContext(parents, payloads)
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return None
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#
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# Merge two {@link ArrayPredictionContext} instances.
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#
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# <p>Different tops, different parents.<br>
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# <embed src="images/ArrayMerge_DiffTopDiffPar.svg" type="image/svg+xml"/></p>
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#
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# <p>Shared top, same parents.<br>
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# <embed src="images/ArrayMerge_ShareTopSamePar.svg" type="image/svg+xml"/></p>
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#
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# <p>Shared top, different parents.<br>
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# <embed src="images/ArrayMerge_ShareTopDiffPar.svg" type="image/svg+xml"/></p>
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#
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# <p>Shared top, all shared parents.<br>
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# <embed src="images/ArrayMerge_ShareTopSharePar.svg" type="image/svg+xml"/></p>
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#
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# <p>Equal tops, merge parents and reduce top to
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# {@link SingletonPredictionContext}.<br>
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# <embed src="images/ArrayMerge_EqualTop.svg" type="image/svg+xml"/></p>
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#/
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def mergeArrays(a:ArrayPredictionContext, b:ArrayPredictionContext, rootIsWildcard:bool, mergeCache:dict):
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if mergeCache is not None:
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previous = mergeCache.get((a,b), None)
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if previous is not None:
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return previous
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previous = mergeCache.get((b,a), None)
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if previous is not None:
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return previous
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# merge sorted payloads a + b => M
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i = 0 # walks a
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j = 0 # walks b
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k = 0 # walks target M array
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mergedReturnStates = [None] * (len(a.returnStates) + len( b.returnStates))
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mergedParents = [None] * len(mergedReturnStates)
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# walk and merge to yield mergedParents, mergedReturnStates
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while i<len(a.returnStates) and j<len(b.returnStates):
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a_parent = a.parents[i]
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b_parent = b.parents[j]
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if a.returnStates[i]==b.returnStates[j]:
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# same payload (stack tops are equal), must yield merged singleton
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payload = a.returnStates[i]
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# $+$ = $
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bothDollars = payload == PredictionContext.EMPTY_RETURN_STATE and \
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a_parent is None and b_parent is None
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ax_ax = (a_parent is not None and b_parent is not None) and a_parent==b_parent # ax+ax -> ax
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if bothDollars or ax_ax:
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mergedParents[k] = a_parent # choose left
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mergedReturnStates[k] = payload
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else: # ax+ay -> a'[x,y]
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mergedParent = merge(a_parent, b_parent, rootIsWildcard, mergeCache)
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mergedParents[k] = mergedParent
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mergedReturnStates[k] = payload
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i += 1 # hop over left one as usual
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j += 1 # but also skip one in right side since we merge
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elif a.returnStates[i]<b.returnStates[j]: # copy a[i] to M
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mergedParents[k] = a_parent
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mergedReturnStates[k] = a.returnStates[i]
|
|
i += 1
|
|
else: # b > a, copy b[j] to M
|
|
mergedParents[k] = b_parent
|
|
mergedReturnStates[k] = b.returnStates[j]
|
|
j += 1
|
|
k += 1
|
|
|
|
# copy over any payloads remaining in either array
|
|
if i < len(a.returnStates):
|
|
for p in range(i, len(a.returnStates)):
|
|
mergedParents[k] = a.parents[p]
|
|
mergedReturnStates[k] = a.returnStates[p]
|
|
k += 1
|
|
else:
|
|
for p in range(j, len(b.returnStates)):
|
|
mergedParents[k] = b.parents[p]
|
|
mergedReturnStates[k] = b.returnStates[p]
|
|
k += 1
|
|
|
|
# trim merged if we combined a few that had same stack tops
|
|
if k < len(mergedParents): # write index < last position; trim
|
|
if k == 1: # for just one merged element, return singleton top
|
|
merged = SingletonPredictionContext.create(mergedParents[0], mergedReturnStates[0])
|
|
if mergeCache is not None:
|
|
mergeCache[(a,b)] = merged
|
|
return merged
|
|
mergedParents = mergedParents[0:k]
|
|
mergedReturnStates = mergedReturnStates[0:k]
|
|
|
|
merged = ArrayPredictionContext(mergedParents, mergedReturnStates)
|
|
|
|
# if we created same array as a or b, return that instead
|
|
# TODO: track whether this is possible above during merge sort for speed
|
|
if merged==a:
|
|
if mergeCache is not None:
|
|
mergeCache[(a,b)] = a
|
|
return a
|
|
if merged==b:
|
|
if mergeCache is not None:
|
|
mergeCache[(a,b)] = b
|
|
return b
|
|
combineCommonParents(mergedParents)
|
|
|
|
if mergeCache is not None:
|
|
mergeCache[(a,b)] = merged
|
|
return merged
|
|
|
|
|
|
#
|
|
# Make pass over all <em>M</em> {@code parents}; merge any {@code equals()}
|
|
# ones.
|
|
#/
|
|
def combineCommonParents(parents:list):
|
|
uniqueParents = dict()
|
|
|
|
for p in range(0, len(parents)):
|
|
parent = parents[p]
|
|
if uniqueParents.get(parent, None) is None:
|
|
uniqueParents[parent] = parent
|
|
|
|
for p in range(0, len(parents)):
|
|
parents[p] = uniqueParents[parents[p]]
|
|
|
|
def getCachedPredictionContext(context:PredictionContext, contextCache:PredictionContextCache, visited:dict):
|
|
if context.isEmpty():
|
|
return context
|
|
existing = visited.get(context)
|
|
if existing is not None:
|
|
return existing
|
|
existing = contextCache.get(context)
|
|
if existing is not None:
|
|
visited[context] = existing
|
|
return existing
|
|
changed = False
|
|
parents = [None] * len(context)
|
|
for i in range(0, len(parents)):
|
|
parent = getCachedPredictionContext(context.getParent(i), contextCache, visited)
|
|
if changed or parent is not context.getParent(i):
|
|
if not changed:
|
|
parents = [context.getParent(j) for j in range(len(context))]
|
|
changed = True
|
|
parents[i] = parent
|
|
if not changed:
|
|
contextCache.add(context)
|
|
visited[context] = context
|
|
return context
|
|
|
|
updated = None
|
|
if len(parents) == 0:
|
|
updated = PredictionContext.EMPTY
|
|
elif len(parents) == 1:
|
|
updated = SingletonPredictionContext.create(parents[0], context.getReturnState(0))
|
|
else:
|
|
updated = ArrayPredictionContext(parents, context.returnStates)
|
|
|
|
contextCache.add(updated)
|
|
visited[updated] = updated
|
|
visited[context] = updated
|
|
|
|
return updated
|
|
|
|
|
|
# # extra structures, but cut/paste/morphed works, so leave it.
|
|
# # seems to do a breadth-first walk
|
|
# public static List<PredictionContext> getAllNodes(PredictionContext context) {
|
|
# Map<PredictionContext, PredictionContext> visited =
|
|
# new IdentityHashMap<PredictionContext, PredictionContext>();
|
|
# Deque<PredictionContext> workList = new ArrayDeque<PredictionContext>();
|
|
# workList.add(context);
|
|
# visited.put(context, context);
|
|
# List<PredictionContext> nodes = new ArrayList<PredictionContext>();
|
|
# while (!workList.isEmpty()) {
|
|
# PredictionContext current = workList.pop();
|
|
# nodes.add(current);
|
|
# for (int i = 0; i < current.size(); i++) {
|
|
# PredictionContext parent = current.getParent(i);
|
|
# if ( parent!=null && visited.put(parent, parent) == null) {
|
|
# workList.push(parent);
|
|
# }
|
|
# }
|
|
# }
|
|
# return nodes;
|
|
# }
|
|
|
|
# ter's recursive version of Sam's getAllNodes()
|
|
def getAllContextNodes(context:PredictionContext, nodes:list=None, visited:dict=None):
|
|
if nodes is None:
|
|
nodes = list()
|
|
return getAllContextNodes(context, nodes, visited)
|
|
elif visited is None:
|
|
visited = dict()
|
|
return getAllContextNodes(context, nodes, visited)
|
|
else:
|
|
if context is None or visited.get(context, None) is not None:
|
|
return nodes
|
|
visited.put(context, context)
|
|
nodes.add(context)
|
|
for i in range(0, len(context)):
|
|
getAllContextNodes(context.getParent(i), nodes, visited)
|
|
return nodes
|
|
|