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Class TestMonitor

test/network/test_monitors.py:9–45  ·  view source on GitHub ↗

Testing Monitor object.

Source from the content-addressed store, hash-verified

7
8
9class TestMonitor:
10 """
11 Testing Monitor object.
12 """
13
14 network = Network()
15
16 inpt = Input(75)
17 network.add_layer(inpt, name="X")
18 _if = IFNodes(25)
19 network.add_layer(_if, name="Y")
20 conn = Connection(inpt, _if, w=torch.rand(inpt.n, _if.n))
21 network.add_connection(conn, source="X", target="Y")
22
23 inpt_mon = Monitor(inpt, state_vars=["s"])
24 network.add_monitor(inpt_mon, name="X")
25 _if_mon = Monitor(_if, state_vars=["s", "v"])
26 network.add_monitor(_if_mon, name="Y")
27
28 network.run(inputs={"X": torch.bernoulli(torch.rand(100, inpt.n))}, time=100)
29
30 assert inpt_mon.get("s").size() == torch.Size([100, 1, inpt.n])
31 assert _if_mon.get("s").size() == torch.Size([100, 1, _if.n])
32 assert _if_mon.get("v").size() == torch.Size([100, 1, _if.n])
33
34 del network.monitors["X"], network.monitors["Y"]
35
36 inpt_mon = Monitor(inpt, state_vars=["s"], time=500)
37 network.add_monitor(inpt_mon, name="X")
38 _if_mon = Monitor(_if, state_vars=["s", "v"], time=500)
39 network.add_monitor(_if_mon, name="Y")
40
41 network.run(inputs={"X": torch.bernoulli(torch.rand(500, inpt.n))}, time=500)
42
43 assert inpt_mon.get("s").size() == torch.Size([500, 1, inpt.n])
44 assert _if_mon.get("s").size() == torch.Size([500, 1, _if.n])
45 assert _if_mon.get("v").size() == torch.Size([500, 1, _if.n])
46
47
48class TestNetworkMonitor:

Callers 1

test_monitors.pyFile · 0.85

Calls 10

NetworkClass · 0.90
InputClass · 0.90
IFNodesClass · 0.90
ConnectionClass · 0.90
MonitorClass · 0.90
add_layerMethod · 0.80
add_connectionMethod · 0.80
add_monitorMethod · 0.80
runMethod · 0.80
getMethod · 0.45

Tested by

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