331 lines
13 KiB
Python
331 lines
13 KiB
Python
from collections import defaultdict
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from migen.fhdl.std import *
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from migen.genlib.misc import optree
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from migen.flow.actor import *
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from migen.flow import plumbing
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# Abstract actors mean that the actor class should be instantiated with the parameters
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# from the dictionary. They are needed to enable actor duplication or sharing during
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# elaboration, and automatic parametrization of plumbing actors.
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class AbstractActor:
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def __init__(self, actor_class, parameters=dict(), name=None):
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self.actor_class = actor_class
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self.parameters = parameters
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self.name = name
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self.busy = Signal()
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def create_instance(self):
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return self.actor_class(**self.parameters)
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def __repr__(self):
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r = "<abstract " + self.actor_class.__name__
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if self.name is not None:
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r += ": " + self.name
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r += ">"
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return r
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class MultiDiGraph:
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def __init__(self):
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self.edges = defaultdict(list)
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self.incoming = defaultdict(set)
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self.outgoing = defaultdict(set)
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self.nodes = set()
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def add_edge(self, a, b, **edge):
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self.edges[(a, b)].append(edge)
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self.incoming[b].add(a)
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self.outgoing[a].add(b)
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self.nodes |= {a, b}
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def __iter__(self):
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return iter(self.nodes)
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def __len__(self):
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return len(self.nodes)
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def edges_iter(self, data=True):
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assert data
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for (a, b), edges in self.edges.items():
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for edge in edges:
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yield a, b, edge
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def get_edge_data(self, a, b):
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return dict(enumerate(self.edges[(a, b)]))
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def add_node(self, node):
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self.nodes.add(node)
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def remove_node(self, node):
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for i in self.incoming.pop(node):
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del self.edges[(i, node)]
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self.outgoing[i].remove(node)
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for i in self.outgoing.pop(node):
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del self.edges[(node, i)]
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self.incoming[i].remove(node)
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self.nodes.remove(node)
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def remove_edge(self, a, b, key):
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e = self.edges[(a, b)]
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del e[key]
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if not e:
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self.incoming[b].remove(a)
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self.outgoing[a].remove(b)
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def in_edges(self, sink, data=True):
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assert data
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e = []
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for source in self.incoming[sink]:
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for edge in self.edges[(source, sink)]:
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e.append((source, sink, edge))
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return e
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def out_edges(self, source, data=True):
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assert data
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e = []
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for sink in self.outgoing[source]:
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for edge in self.edges[(source, sink)]:
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e.append((source, sink, edge))
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return e
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# TODO: rewrite this without non-determinism
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class DataFlowGraph(MultiDiGraph):
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def __init__(self):
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MultiDiGraph.__init__(self)
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self.elaborated = False
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self.abstract_busy_signals = dict()
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def add_connection(self, source_node, sink_node,
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source_ep=None, sink_ep=None, # default: assume nodes have 1 source/sink and use that one
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source_subr=None, sink_subr=None): # default: use whole record
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self.add_edge(source_node, sink_node,
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source=source_ep, sink=sink_ep,
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source_subr=source_subr, sink_subr=sink_subr)
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def add_buffered_connection(self, source_node, sink_node,
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source_ep=None, sink_ep=None,
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source_subr=None, sink_subr=None):
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buf = AbstractActor(plumbing.Buffer)
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self.add_connection(source_node, buf, source_ep=source_ep, source_subr=source_subr)
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self.add_connection(buf, sink_node, sink_ep=sink_ep, sink_subr=sink_subr)
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def add_pipeline(self, *nodes):
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for n1, n2 in zip(nodes, nodes[1:]):
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self.add_connection(n1, n2)
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def del_connections(self, source_node, sink_node, data_requirements):
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edges_to_delete = []
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edge_data = self.get_edge_data(source_node, sink_node)
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if edge_data is None:
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# the two nodes are already completely disconnected
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return
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for key, data in edge_data.items():
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if all(k not in data_requirements or data_requirements[k] == v
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for k, v in data.items()):
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edges_to_delete.append(key)
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for key in edges_to_delete:
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self.remove_edge(source_node, sink_node, key)
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def replace_actor(self, old, new):
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self.add_node(new)
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for xold, v, data in self.out_edges(old, data=True):
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self.add_edge(new, v, **data)
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for u, xold, data in self.in_edges(old, data=True):
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self.add_edge(u, new, **data)
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self.remove_node(old)
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def instantiate(self, actor):
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inst = actor.create_instance()
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self.abstract_busy_signals[id(inst)] = actor.busy
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self.replace_actor(actor, inst)
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# Returns a dictionary
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# source -> [sink1, ..., sinkn]
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# source element is a (node, endpoint) pair.
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# sink elements are (node, endpoint, source subrecord, sink subrecord) triples.
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def _source_to_sinks(self):
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d = dict()
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for u, v, data in self.edges_iter(data=True):
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el_src = (u, data["source"])
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el_dst = (v, data["sink"], data["source_subr"], data["sink_subr"])
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if el_src in d:
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d[el_src].append(el_dst)
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else:
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d[el_src] = [el_dst]
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return d
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# Returns a dictionary
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# sink -> [source1, ... sourcen]
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# sink element is a (node, endpoint) pair.
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# source elements are (node, endpoint, sink subrecord, source subrecord) triples.
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def _sink_to_sources(self):
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d = dict()
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for u, v, data in self.edges_iter(data=True):
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el_src = (u, data["source"], data["sink_subr"], data["source_subr"])
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el_dst = (v, data["sink"])
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if el_dst in d:
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d[el_dst].append(el_src)
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else:
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d[el_dst] = [el_src]
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return d
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# List sources that feed more than one sink.
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def _list_divergences(self):
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d = self._source_to_sinks()
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return dict((k, v) for k, v in d.items() if len(v) > 1)
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# A graph is abstract if any of these conditions is met:
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# (1) A node is an abstract actor.
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# (2) A subrecord is used.
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# (3) A single source feeds more than one sink.
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# NB: It is not allowed for a single sink to be fed by more than one source
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# (except with subrecords, i.e. when a combinator is used)
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def is_abstract(self):
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return any(isinstance(x, AbstractActor) for x in self) \
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or any(d["source_subr"] is not None or d["sink_subr"] is not None
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for u, v, d in self.edges_iter(data=True)) \
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or bool(self._list_divergences())
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def _eliminate_subrecords_and_divergences(self):
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# Insert combinators.
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for (dst_node, dst_endpoint), sources in self._sink_to_sources().items():
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if len(sources) > 1 or sources[0][2] is not None:
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# build combinator
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# "layout" is filled in during instantiation
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subrecords = [dst_subrecord for src_node, src_endpoint, dst_subrecord, src_subrecord in sources]
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combinator = AbstractActor(plumbing.Combinator, {"subrecords": subrecords})
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# disconnect source1 -> sink ... sourcen -> sink
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# connect source1 -> combinator_sink1 ... sourcen -> combinator_sinkn
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for n, (src_node, src_endpoint, dst_subrecord, src_subrecord) in enumerate(sources):
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self.del_connections(src_node, dst_node,
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{"source": src_endpoint, "sink": dst_endpoint})
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self.add_connection(src_node, combinator,
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src_endpoint, "sink{0}".format(n), source_subr=src_subrecord)
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# connect combinator_source -> sink
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self.add_connection(combinator, dst_node, "source", dst_endpoint)
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# Insert splitters.
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for (src_node, src_endpoint), sinks in self._source_to_sinks().items():
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if len(sinks) > 1 or sinks[0][2] is not None:
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subrecords = [src_subrecord for dst_node, dst_endpoint, src_subrecord, dst_subrecord in sinks]
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splitter = AbstractActor(plumbing.Splitter, {"subrecords": subrecords})
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# disconnect source -> sink1 ... source -> sinkn
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# connect splitter_source1 -> sink1 ... splitter_sourcen -> sinkn
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for n, (dst_node, dst_endpoint, src_subrecord, dst_subrecord) in enumerate(sinks):
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self.del_connections(src_node, dst_node,
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{"source": src_endpoint, "sink": dst_endpoint})
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self.add_connection(splitter, dst_node,
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"source{0}".format(n), dst_endpoint)
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# connect source -> splitter_sink
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self.add_connection(src_node, splitter, src_endpoint, "sink")
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def _infer_plumbing_layout(self):
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while True:
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ap = [a for a in self if isinstance(a, AbstractActor) and a.actor_class in plumbing.actors]
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if not ap:
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break
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for a in ap:
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in_edges = self.in_edges(a, data=True)
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out_edges = self.out_edges(a, data=True)
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if a.actor_class in plumbing.layout_sink and len(in_edges) == 1:
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other, me, data = in_edges[0]
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if isinstance(other, AbstractActor):
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continue
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other_ep = data["source"]
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if other_ep is None:
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other_ep = get_single_ep(other, Source)[1]
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else:
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other_ep = getattr(other, other_ep)
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elif a.actor_class in plumbing.layout_source and len(out_edges) == 1:
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me, other, data = out_edges[0]
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if isinstance(other, AbstractActor):
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continue
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other_ep = data["sink"]
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if other_ep is None:
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other_ep = get_single_ep(other, Sink)[1]
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else:
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other_ep = getattr(other, other_ep)
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else:
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raise AssertionError
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layout = other_ep.payload.layout
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a.parameters["layout"] = layout
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self.instantiate(a)
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def _instantiate_actors(self):
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# 1. instantiate all abstract non-plumbing actors
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for actor in list(self):
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if isinstance(actor, AbstractActor) and actor.actor_class not in plumbing.actors:
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self.instantiate(actor)
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# 2. infer plumbing layout and instantiate plumbing
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self._infer_plumbing_layout()
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# 3. resolve default eps
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for u, v, d in self.edges_iter(data=True):
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if d["source"] is None:
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d["source"] = get_single_ep(u, Source)[0]
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if d["sink"] is None:
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d["sink"] = get_single_ep(v, Sink)[0]
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# Elaboration turns an abstract DFG into a physical one.
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# Pass 1: eliminate subrecords and divergences
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# by inserting Combinator/Splitter actors
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# Pass 2: run optimizer (e.g. share and duplicate actors)
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# Pass 3: instantiate all abstract actors and explicit "None" endpoints
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def elaborate(self, optimizer=None):
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if self.elaborated:
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return
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self.elaborated = True
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self._eliminate_subrecords_and_divergences()
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if optimizer is not None:
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optimizer(self)
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self._instantiate_actors()
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class CompositeActor(Module):
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def __init__(self, dfg):
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dfg.elaborate()
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# expose unconnected endpoints
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uc_eps_by_node = dict((node, get_endpoints(node)) for node in dfg)
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for u, v, d in dfg.edges_iter(data=True):
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uc_eps_u = uc_eps_by_node[u]
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source = d["source"]
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try:
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del uc_eps_u[source]
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except KeyError:
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pass
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uc_eps_v = uc_eps_by_node[v]
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sink = d["sink"]
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try:
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del uc_eps_v[sink]
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except KeyError:
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pass
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for node, uc_eps in uc_eps_by_node.items():
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for k, v in uc_eps.items():
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assert(not hasattr(self, k))
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setattr(self, k, v)
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# connect abstract busy signals
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for node in dfg:
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try:
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abstract_busy_signal = dfg.abstract_busy_signals[id(node)]
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except KeyError:
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pass
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else:
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self.comb += abstract_busy_signal.eq(node.busy)
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# generate busy signal
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self.busy = Signal()
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self.comb += self.busy.eq(optree("|", [node.busy for node in dfg]))
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# claim ownership of sub-actors and establish connections
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for node in dfg:
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self.submodules += node
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for u, v, d in dfg.edges_iter(data=True):
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ep_src = getattr(u, d["source"])
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ep_dst = getattr(v, d["sink"])
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self.comb += ep_src.connect_flat(ep_dst)
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