def test_debug(self):
nn = ng.NNModule()
dfg = nn.dataFlow
dfg.createNode(ng.NeuralNetData("X"))
dfg.createNode(ng.NeuralNetData("W"))
dfg.createNode(ng.NeuralNetOperator("Op"))
ng.render(nn.dataFlow)
def test_edges_simple(self):
nn = ng.NNModule()
dfg = nn.dataFlow
x = dfg.createNode(ng.NeuralNetData("X"))
w = dfg.createNode(ng.NeuralNetData("W"))
op = dfg.createNode(ng.NeuralNetOperator("Op"))
with self.assertRaises(Exception):
dfg.createEdge(x, w)
dfg.createEdge(op, w)
dfg.createEdge(x, op)
def test_distributed_annotations(self):
nn = ng.NNModule()
key = nn.dataFlow.createNode(ng.NeuralNetData("key"))
length = nn.dataFlow.createNode(ng.NeuralNetData("length"))
node = nn.dataFlow.createNode(ng.NeuralNetOperator("TestOp"))
annot = ng.Annotation()
annot.setKeyNode(key)
annot.setLengthNode(length)
annot.setComponentLevels(["", "test", "woot"])
node.setAnnotation(annot)
new_annot = node.getAnnotation()
#assert new_annot.getLengthNode() == length
assert new_annot.getKeyNode() == key
assert len(new_annot.getComponentLevels()) == 3
assert new_annot.getComponentLevels()[0] == ""
assert new_annot.getComponentLevels()[2] == "woot"
def test_delete_subgraph(self):
mg = ng.NNMatchGraph()
test2m = mg.createNode(ng.NeuralNetOperator("test2"), strict=True)
xm = mg.createNode(ng.NeuralNetData("X"), strict=True)
testm = mg.createNode(ng.NeuralNetOperator("test"))
mg.createEdge(test2m, xm)
mg.createEdge(xm, testm)
nn = ng.NNModule()
test2 = nn.dataFlow.createNode(ng.NeuralNetOperator("test2"))
x = nn.dataFlow.createNode(ng.NeuralNetData("X"))
test = nn.dataFlow.createNode(ng.NeuralNetOperator("test"))
nn.dataFlow.createEdge(test2, x)
nn.dataFlow.createEdge(x, test)
for m in nn.match(mg):
match = m
nn.deleteSubgraph(match)
assert len(nn.controlFlow) == 0
def test_replace_all_uses_with(self):
net = core.Net("name")
net.FC(["X", "W"], ["Y"])
net.FC(["X", "W2"], ["Y2"])
nn = ng.NNModule(net)
fc = nn.controlFlow[0]
test_tensor = nn.dataFlow.createNode(ng.NeuralNetData("T"))
nn.replaceAllUsesWith(fc.inputs[0], test_tensor)
for op in nn.controlFlow:
assert op.inputs[0].name == "T"
def test_replace_subraph(self):
mg = ng.NNMatchGraph()
test2m = mg.createNode(ng.NeuralNetOperator("test2"), strict=True)
xm = mg.createNode(ng.NeuralNetData("X"), strict=True)
testm = mg.createNode(ng.NeuralNetOperator("test"))
mg.createEdge(test2m, xm)
mg.createEdge(xm, testm)
nn = ng.NNModule()
test2 = nn.dataFlow.createNode(ng.NeuralNetOperator("test2"))
x = nn.dataFlow.createNode(ng.NeuralNetData("X"))
test = nn.dataFlow.createNode(ng.NeuralNetOperator("test"))
nn.dataFlow.createEdge(test2, x)
nn.dataFlow.createEdge(x, test)
for m in nn.match(mg):
match = m
new_op = nn.dataFlow.createNode(ng.NeuralNetOperator("new_op"))
nn.replaceSubgraph(match, new_op, [], [])
assert len(nn.controlFlow) == 1
assert nn.controlFlow[0].name == "new_op"
def test_match_graph(self):
mg = ng.NNMatchGraph()
test2m = mg.createNode(ng.NeuralNetOperator("test2"), strict=True)
xm = mg.createNode(ng.NeuralNetData("X"), strict=True)
testm = mg.createNode(ng.NeuralNetOperator("test"))
mg.createEdge(test2m, xm)
mg.createEdge(xm, testm)
nn = ng.NNModule()
test2 = nn.dataFlow.createNode(ng.NeuralNetOperator("test2"))
x = nn.dataFlow.createNode(ng.NeuralNetData("X"))
test = nn.dataFlow.createNode(ng.NeuralNetOperator("test"))
nn.dataFlow.createEdge(test2, x)
nn.dataFlow.createEdge(x, test)
count = 0
for match in nn.match(mg):
print(len(match))
assert len(match) == 3
count += 1
assert count == 1
def test_match_graph_node(self):
mg = ng.NNMatchGraph()
mg.createNode(ng.NeuralNetOperator("test"))
nn = ng.NNModule()
test = nn.dataFlow.createNode(ng.NeuralNetOperator("test"))
x = nn.dataFlow.createNode(ng.NeuralNetData("X"))
nn.dataFlow.createEdge(x, test)
count = 0
for match in nn.match(mg):
assert len(match) == 1
count += 1
assert count == 1
def test_edges_simple(self):
nn = ng.NNModule()
dfg = nn.dataFlow
x = dfg.createNode(ng.NeuralNetData("X"))
w = dfg.createNode(ng.NeuralNetData("W"))
op = dfg.createNode(ng.NeuralNetOperator("Op"))
with self.assertRaises(Exception):
dfg.createEdge(x, w)
dfg.createEdge(op, w)
dfg.createEdge(x, op)
# Dot generation
assert(str(dfg).startswith("digraph G"))
# subgraph
sg = ng.NNSubgraph()
sg.addNode(x)
sg.addNode(op)
sg.induceEdges()
assert len(sg) == 2
# subgraph dot generation
assert(str(sg).startswith("digraph G"))
def test_match_graph_node_strict(self):
mg = ng.NNMatchGraph()
mg.createNode(ng.NeuralNetOperator("test"), strict=True)
nn = ng.NNModule()
test = nn.dataFlow.createNode(ng.NeuralNetOperator("test"))
x = nn.dataFlow.createNode(ng.NeuralNetData("X"))
nn.dataFlow.createEdge(test, x)
count = 0
for match in nn.match(mg):
assert len(match) == 1
count += 1
with self.assertRaises(Exception):
assert count == 1
def test_match_graph_node(self):
mg = ng.NNMatchGraph()
mg.createNode(ng.NeuralNetOperator("test"))
nn = ng.NNModule()
test = nn.dataFlow.createNode(ng.NeuralNetOperator("test"))
x = nn.dataFlow.createNode(ng.NeuralNetData("X"))
nn.dataFlow.createEdge(x, test)
count = 0
for match in nn.match(mg):
assert len(match) == 1
count += 1
# Dot generation of subgraph
assert(str(match).startswith("digraph G"))
assert count == 1
def test_edges_complex(self, size):
random.seed(1337)
nn = ng.NNModule()
dfg = nn.dataFlow
data = []
ops = []
for _ in range(size):
data.append(dfg.createNode(ng.NeuralNetData("X")))
for i in range(size):
ops.append(dfg.createNode(ng.NeuralNetOperator("Op" + str(i))))
for i in range(size):
for j in range(size):
if bool(random.getrandbits(1)):
dfg.createEdge(data[i], ops[j])
def test_simple(self):
nn = ng.NNModule()
dfg = nn.dataFlow
dfg.createNode(ng.NeuralNetData("X"))
dfg.createNode(ng.NeuralNetOperator("FC"))
assert len(nn.dataFlow.getMutableNodes()) == 2
