def __init__(self):
self.symTable = {}
self.iterTable = {}
self.constTable = {}
self.linkTable = {}
self.gradientTable = {}
self.dfg = DataFlowGraph()
self.funcTypeTable = {}
self.parseTree = None
def fromList(self, l):
dfg = DataFlowGraph()
for nodeDict in l:
node = DFGNode()
node.fromDict(nodeDict)
dfg.nodes.insert(node.id, node)
for node in dfg.nodes:
children = node.children
for index, childId in enumerate(children):
children[index] = dfg.get(childId)
parents = node.parents
for index, parentId in enumerate(parents):
parents[index] = dfg.get(parentId)
return dfg
def create(self, tree):
self.parseTree = tree
self.dfg = DataFlowGraph()
#self.funcTypeTable = {}
# Create source and sink nodes first.
source = DFGNode()
source.operation = 'source'
self.dfg.add(source)
sink = DFGNode()
sink.operation = 'sink'
sink.dist2sink = 0
self.dfg.add(sink)
# Create hash tables for Data_Declarations
# print("******Before DFG******")
self.constTable = self.createConstTable()
self.iterTable = self.createIterTable(self.constTable)
self.symTable, self.gradientTable = self.createSymbolTable(
self.constTable)
self.funcTypeTable = self.createFuncTypeTable()
# print('const table',self.constTable)
# print('iter table',self.iterTable)
# print('symTable',self.symTable)
# print('funcTypeTable',self.funcTypeTable)
# print('gradientTable', self.gradientTable)
# print("================================\n\n")
# Get statList for all Stats
statList = self.parseTree.getChild(1)
# Creation of DFG.
if statList.children is not None:
for stat in statList.children:
resultNodes = self.statTraversal(stat)
# Append SGD
for g in self.linkTable:
leftBound = g.find("[") + 1
rightBound = g.rfind("]")
iterList = g[leftBound:rightBound].split('][')
for i in range(len(iterList)):
if not iterList[i].isdigit():
iterList[i] = self.constTable[iterList[i]]
if len(iterList) is 0:
mult = DFGNode()
mult.operation = "*"
#mult.dataType = 'gradient'
mult.dataType = None
self.dfg.add(mult)
self.connectNode(self.symTable[g], mult)
self.connectNode(symTable["mu"], mult)
sub = DFGNode()
sub.operation = "-"
sub.dataType = 'model'
self.dfg.add(sub)
self.connectNode(mult, sub)
self.connectNode(self.symTable[self.linkTable[g]], sub)
self.symTable[self.symTable[self.linkTable[g]]] = sub
else:
for i in range(iterList[0]):
if len(iterList) is 1:
gSym = g[0:g.find('[')] + '[' + str(i) + ']'
#print(gSym)
if gSym in self.symTable:
mult = DFGNode()
mult.operation = "*"
#mult.dataType = 'gradient'
mult.dataType = None
self.dfg.add(mult)
self.connectNode(self.symTable[gSym], mult)
self.connectNode(self.symTable["mu"], mult)
sub = DFGNode()
sub.operation = "-"
sub.dataType = 'model'
self.dfg.add(sub)
wSym = self.linkTable[g] + '[' + str(i) + ']'
self.connectNode(mult, sub)
self.connectNode(self.symTable[wSym], sub)
self.symTable[wSym] = sub
else:
for j in range(iterList[1]):
gSym = g[0:g.find('[')] + '[' + str(
i) + '][' + str(j) + ']'
if gSym in self.symTable:
mult = DFGNode()
mult.operation = "*"
#mult.dataType = 'gradient'
mult.dataType = None
self.dfg.add(mult)
self.connectNode(self.symTable[gSym], mult)
self.connectNode(self.symTable["mu"], mult)
sub = DFGNode()
sub.operation = "-"
sub.dataType = 'model'
self.dfg.add(sub)
wSym = self.linkTable[g] + '[' + str(
i) + '][' + str(j) + ']'
self.connectNode(mult, sub)
self.connectNode(self.symTable[wSym], sub)
self.symTable[wSym] = sub
# Needs to connect correct outputs to the sink node
for node in self.symTable.values(): # Connect outputs
if len(node.children) is 0 and len(node.parents) is not 1:
self.connectNode(node, self.dfg.get(1))
# Calculates all the distances to sink
self.setDist2sink(sink)
# Remove useless nodes
# self.dfg.updateId()
removedNodes = []
for node in self.dfg.nodes:
if node.dist2sink is None:
for child in node.children:
child.parents.remove(node)
for parent in node.parents:
parent.children.remove(node)
removedNodes.append(node)
for node in removedNodes:
self.dfg.remove(node)
# Print and save
self.dfg.updateId()
# for val in self.dfg.nodes:
# print(val)
# print("******After DFG******")
# print('const table',self.constTable)
# print('iter table',self.iterTable)
# print('symTable',self.symTable)
# self.dfg.save('./dfg.json')
return self.dfg