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108 lines
2.6 KiB
Python
108 lines
2.6 KiB
Python
from cmsisdsp.cg.static.scheduler import *
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### Define new types of Nodes
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class ProcessingNode(GenericNode):
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def __init__(self,name,theType,inLength,outLength):
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GenericNode.__init__(self,name)
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self.addInput("i",theType,inLength)
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self.addOutput("oa",theType,outLength)
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self.addOutput("ob",theType,outLength)
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@property
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def typeName(self):
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return "ProcessingNode"
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class Sink(GenericSink):
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def __init__(self,name,theType,inLength):
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GenericSink.__init__(self,name)
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self.addInput("i",theType,inLength)
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@property
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def typeName(self):
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return "Sink"
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class Source(GenericSource):
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def __init__(self,name,theType,inLength):
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GenericSource.__init__(self,name)
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self.addOutput("o",theType,inLength)
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@property
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def typeName(self):
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return "Source"
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### Define nodes
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# Node datatype
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# WARNING : In Python there is reference semantic for
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# the objects. But in C++, the struct have value semantic.
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# So in Python implementation of the node, the reference
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# shoudl never be shared.
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# Modify the fields of the objects, or create a totally new
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# object.
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complexType=CStructType("complex","MyComplex",8)
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src=Source("source",complexType,5)
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b=ProcessingNode("filter",complexType,7,5)
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b.addLiteralArg(4)
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b.addLiteralArg("Test")
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b.addVariableArg("someVariable")
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na = Sink("sa",complexType,5)
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nb = Sink("sb",complexType,5)
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nc = Sink("sc",complexType,5)
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nd = Sink("sd",complexType,5)
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#dup=Duplicate3("dup",complexType,5)
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g = Graph()
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g.connect(src.o,b.i)
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#g.connect(b.o,dup.i)
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#g.connect(dup.oa,na.i)
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#g.connect(dup.ob,nb.i)
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#g.connect(dup.oc,nc.i)
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g.connect(b.oa,na.i)
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g.connect(b.oa,nb.i)
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g.connect(b.oa,nc.i)
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g.connect(b.ob,nd.i)
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GEN_PYTHON = False
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print("Generate graphviz and code")
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conf=Configuration()
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#conf.dumpSchedule = True
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sched = g.computeSchedule(conf)
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print("Schedule length = %d" % sched.scheduleLength)
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print("Memory usage %d bytes" % sched.memory)
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# Generation of the schedule is modifying the original graph
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# (Introduction of duplicate nodes ...)
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# So we cannot reuse the graph to compute the Python and the C
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# code generation
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conf.debugLimit=1
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conf.cOptionalArgs="int someVariable"
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#conf.codeArray=True
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conf.memoryOptimization=True
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if not GEN_PYTHON:
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# C++ implementation
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sched.ccode("generated",conf)
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else:
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# Python implementation
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conf.pyOptionalArgs="someVariable"
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sched.pythoncode(".",config=conf)
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# When true it is displaying the name of the FIFO buffer
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# When false it is displaying the size of the FIFO (default)
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conf.displayFIFOBuf=False
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with open("test.dot","w") as f:
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sched.graphviz(f,config=conf)
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