def test_mixed_parallel_flow(self):
"""Test a ParallelBiFlow with both standard and BiNodes."""
flow = ParallelBiFlow([mdp.nodes.PCANode(output_dim=8), SFABiNode(output_dim=5), SFA2BiNode(output_dim=20)])
data_iterables = [[n.random.random((20, 10)) for _ in range(6)]] * 3
scheduler = mdp.parallel.Scheduler()
flow.train(data_iterables, scheduler=scheduler)
x = n.random.random([100, 10])
flow.execute(x)
iterator = [n.random.random((20, 10)) for _ in range(6)]
flow.execute(iterator, scheduler=scheduler)
scheduler.shutdown()
def test_use_copies_msg(self):
"""Test the correct reaction to an outgoing use_copies message."""
stop_result = ({"clonelayer" + MSG_ID_SEP + "use_copies": True},
EXIT_TARGET)
stop_sfa_node = SFABiNode(stop_result=stop_result,
input_dim=10, output_dim=3)
biflownode = BiFlowNode(BiFlow([stop_sfa_node]))
clonelayer = ParallelCloneBiLayer(node=biflownode,
n_nodes=3,
use_copies=False,
node_id="clonelayer")
data = [[n.random.random((100,30)) for _ in range(5)]]
biflow = ParallelBiFlow([clonelayer])
biflow.train(data, scheduler=mdp.parallel.Scheduler())
assert clonelayer.use_copies is True
def test_mixed_parallel_flow(self):
"""Test a ParallelBiFlow with both standard and BiNodes."""
flow = ParallelBiFlow([
mdp.nodes.PCANode(output_dim=8),
SFABiNode(output_dim=5),
SFA2BiNode(output_dim=20)
])
data_iterables = [[n.random.random((20, 10)) for _ in range(6)]] * 3
scheduler = mdp.parallel.Scheduler()
flow.train(data_iterables, scheduler=scheduler)
x = n.random.random([100, 10])
flow.execute(x)
iterator = [n.random.random((20, 10)) for _ in range(6)]
flow.execute(iterator, scheduler=scheduler)
scheduler.shutdown()
def test_nonparallel_flow(self):
"""Test a ParallelBiFlow with standard nodes."""
flow = ParallelBiFlow([mdp.nodes.SFANode(output_dim=5),
mdp.nodes.PolynomialExpansionNode(degree=3),
mdp.nodes.SFANode(output_dim=20)])
data_iterables = [[n.random.random((20,10)) for _ in range(6)],
None,
[n.random.random((20,10)) for _ in range(6)]]
scheduler = mdp.parallel.Scheduler()
flow.train(data_iterables, scheduler=scheduler)
x = n.random.random([100,10])
flow.execute(x)
iterator = [n.random.random((20,10)) for _ in range(6)]
flow.execute(iterator, scheduler=scheduler)
scheduler.shutdown()
def test_nonparallel_flow(self):
"""Test a ParallelBiFlow with standard nodes."""
flow = ParallelBiFlow([
mdp.nodes.SFANode(output_dim=5),
mdp.nodes.PolynomialExpansionNode(degree=3),
mdp.nodes.SFANode(output_dim=20)
])
data_iterables = [[n.random.random((20, 10)) for _ in range(6)], None,
[n.random.random((20, 10)) for _ in range(6)]]
scheduler = mdp.parallel.Scheduler()
flow.train(data_iterables, scheduler=scheduler)
x = n.random.random([100, 10])
flow.execute(x)
iterator = [n.random.random((20, 10)) for _ in range(6)]
flow.execute(iterator, scheduler=scheduler)
scheduler.shutdown()
def test_use_copies_msg(self):
"""Test the correct reaction to an outgoing use_copies message."""
stop_result = ({
"clonelayer" + MSG_ID_SEP + "use_copies": True
}, EXIT_TARGET)
stop_sfa_node = SFABiNode(stop_result=stop_result,
input_dim=10,
output_dim=3)
biflownode = BiFlowNode(BiFlow([stop_sfa_node]))
clonelayer = ParallelCloneBiLayer(node=biflownode,
n_nodes=3,
use_copies=False,
node_id="clonelayer")
data = [[n.random.random((100, 30)) for _ in range(5)]]
biflow = ParallelBiFlow([clonelayer])
biflow.train(data, scheduler=mdp.parallel.Scheduler())
assert clonelayer.use_copies is True
def test_parallel_process(self):
"""Test training and execution with multiple training phases.
The node with multiple training phases is a hinet.FlowNode.
"""
sfa_node = mdp.nodes.SFANode(input_dim=10, output_dim=8)
sfa2_node = mdp.nodes.SFA2Node(input_dim=8, output_dim=6)
flow = ParallelBiFlow([sfa_node, sfa2_node])
data_iterables = [[n.random.random((30, 10)) for _ in range(6)], [n.random.random((30, 10)) for _ in range(7)]]
scheduler = mdp.parallel.ProcessScheduler(n_processes=2)
flow.train(data_iterables, scheduler=scheduler)
flow.execute(data_iterables[1], scheduler=scheduler)
x = n.random.random([100, 10])
flow.execute(x)
iterator = [n.random.random((20, 10)) for _ in range(6)]
flow.execute(iterator, scheduler=scheduler)
scheduler.shutdown()
def test_parallel_process(self):
"""Test training and execution with multiple training phases.
The node with multiple training phases is a hinet.FlowNode.
"""
sfa_node = mdp.nodes.SFANode(input_dim=10, output_dim=8)
sfa2_node = mdp.nodes.SFA2Node(input_dim=8, output_dim=6)
flow = ParallelBiFlow([sfa_node, sfa2_node])
data_iterables = [[n.random.random((30, 10)) for _ in range(6)],
[n.random.random((30, 10)) for _ in range(7)]]
scheduler = mdp.parallel.ProcessScheduler(n_processes=2)
flow.train(data_iterables, scheduler=scheduler)
flow.execute(data_iterables[1], scheduler=scheduler)
x = n.random.random([100, 10])
flow.execute(x)
iterator = [n.random.random((20, 10)) for _ in range(6)]
flow.execute(iterator, scheduler=scheduler)
scheduler.shutdown()