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import mdp
n = mdp.numx
import py.test
from bimdp import BiNode, MSG_ID_SEP, BiFlow, BiClassifier, binode_coroutine
from bimdp.nodes import (
IdentityBiNode, SFABiNode, FDABiNode, SignumBiClassifier
)
from _tools import JumpBiNode
class TestBiNode(object):
def test_msg_parsing1(self):
"""Test the message parsing and recombination."""
class TestBiNode(BiNode):
def _execute(self, x, a, b, d):
self.a = a
self.b = b
self.d = d
return x, {"g": 15, "z": 3}
@staticmethod
def is_trainable(): return False
binode = TestBiNode(node_id="test")
b_key = "test" + MSG_ID_SEP + "b"
d_key = "test" + MSG_ID_SEP + "d"
msg = {"c": 12, b_key: 42, "a": 13, d_key: "bla"}
_, msg = binode.execute(None, msg)
assert "a" in msg
assert b_key not in msg
assert d_key not in msg
assert binode.a == 13
assert binode.b == 42
assert binode.d == "bla"
# test the message combination
assert msg["g"] == 15
assert msg["z"] == 3
def test_msg_parsing2(self):
"""Test that an adressed argument is not found."""
class TestBiNode(BiNode):
def _execute(self, x, a, b):
self.a = a
self.b = b
@staticmethod
def is_trainable(): return False
binode = TestBiNode(node_id="test")
b_key = "test" + MSG_ID_SEP + "b"
# check that the 'd' key which is not an arg gets removed
d_key = "test" + MSG_ID_SEP + "d"
msg = {"c": 12, b_key: 42, "a": 13, d_key: "bla"}
_, out_msg = binode.execute(None, msg)
assert d_key not in out_msg
def test_msg_magic(self):
"""Test that the magic msg argument works."""
class TestBiNode(BiNode):
def _execute(self, x, a, msg, b):
self.a = a
self.b = b
del msg["c"]
msg["f"] = 1
return x, msg
@staticmethod
def is_trainable(): return False
binode = TestBiNode(node_id="test")
b_key = "test" + MSG_ID_SEP + "b"
msg = {"c": 12, b_key: 42, "a": 13}
_, msg = binode.execute(None, msg)
assert "a" in msg
assert "c" not in msg # was deleted in _execute
assert msg["f"] == 1
assert b_key not in msg
assert binode.a == 13
assert binode.b == 42
def test_method_magic(self):
"""Test the magic method message key."""
class TestBiNode(BiNode):
def _test(self, x, a, b):
self.a = a
self.b = b
@staticmethod
def is_trainable(): return False
binode = TestBiNode(node_id="test")
b_key = "test" + MSG_ID_SEP + "b"
msg = {"c": 12, "a": 13, b_key: 42, "method": "test"}
binode.execute(None, msg)
assert "a" in msg
assert b_key not in msg
assert binode.b == 42
def test_target_magic(self):
"""Test the magic target message key."""
class TestBiNode(BiNode):
def _execute(self, x, a, b):
self.a = a
self.b = b
@staticmethod
def is_trainable(): return False
binode = TestBiNode(node_id="test")
b_key = "test" + MSG_ID_SEP + "b"
target_key = "test" + MSG_ID_SEP + "target"
msg = {"c": 12, b_key: 42, "a": 13, target_key: "test2"}
result = binode.execute(None, msg)
assert len(result) == 3
assert result[2] == "test2"
def test_inverse_magic1(self):
"""Test the magic inverse method argument."""
class TestBiNode(BiNode):
def _inverse(self, x, a, b):
self.a = a
self.b = b
y = n.zeros((len(x), self.input_dim))
return y
@staticmethod
def is_trainable(): return False
binode = TestBiNode(node_id="test", input_dim=20, output_dim=10)
b_key = "test" + MSG_ID_SEP + "b"
msg = {"c": 12, "a": 13, b_key: 42, "method": "inverse"}
x = n.zeros((5, binode.output_dim))
result = binode.execute(x, msg)
assert len(result) == 3
assert result[2] == -1
assert result[0].shape == (5, 20)
def test_inverse_magic2(self):
"""Test overriding the magic inverse target."""
class TestBiNode(BiNode):
def _inverse(self, x, a, b):
self.a = a
self.b = b
y = n.zeros((len(x), self.input_dim))
return y, None, "test2"
@staticmethod
def is_trainable(): return False
binode = TestBiNode(node_id="test", input_dim=20, output_dim=10)
b_key = "test" + MSG_ID_SEP + "b"
msg = {"c": 12, "a": 13, b_key: 42, "method": "inverse"}
x = n.zeros((5, binode.output_dim))
result = binode.execute(x, msg)
assert result[2] == "test2"
def test_stoptrain_result1(self):
"""Test that stop_result is handled correctly."""
stop_result = ({"test": 0}, 1)
bi_sfa_node = SFABiNode(stop_result=stop_result,
node_id="testing binode")
assert bi_sfa_node.is_trainable()
x = n.random.random((100,10))
train_result = bi_sfa_node.train(x)
assert train_result == None
assert bi_sfa_node.is_training()
result = bi_sfa_node.stop_training()
assert result == (None,) + stop_result
assert bi_sfa_node.input_dim == 10
assert bi_sfa_node.output_dim == 10
assert bi_sfa_node.dtype == "float64"
def test_stoptrain_result2(self):
"""Test that stop_result is handled correctly for multiple phases."""
stop_result = [({"test": 0}, 1), ({"test2": 0}, 2)]
binode = FDABiNode(stop_result=stop_result,
node_id="testing binode")
x = n.random.random((100,10))
msg = {"labels": n.zeros(len(x))}
binode.train(x, msg)
result = binode.stop_training()
assert result == (None,) + stop_result[0]
binode.train(x, msg)
result = binode.stop_training()
assert result == (None,) + stop_result[1]
def test_stop_training_execute(self):
"""Test the magic execute method argument for stop_training."""
class TestBiNode(BiNode):
def _train(self, x): pass
def _execute(self, x, a):
self.a = a
self.x = x
y = n.zeros((len(x), self.output_dim))
return y
binode = TestBiNode(input_dim=20, output_dim=10)
x = n.ones((5, binode.input_dim))
binode.train(x)
msg = {"x": x, "a": 13, "method": "execute"}
result = binode.stop_training(msg)
assert n.all(binode.x == x)
assert binode.x.shape == (5, binode.input_dim)
assert binode.a == 13
assert len(result) == 2
assert result[0].shape == (5, binode.output_dim)
assert not n.any(result[0])
def test_stop_training_inverse(self):
"""Test the magic inverse method argument for stop_training."""
class TestBiNode(BiNode):
def _train(self, x): pass
def _inverse(self, x, a):
self.a = a
self.x = x
y = n.zeros((len(x), self.input_dim))
return y
binode = TestBiNode(input_dim=20, output_dim=10)
binode.train(n.ones((5, binode.input_dim)))
x = n.ones((5, binode.output_dim))
msg = {"x": x, "a": 13, "method": "inverse"}
result = binode.stop_training(msg)
assert n.all(binode.x == x)
assert binode.x.shape == (5, binode.output_dim)
assert binode.a == 13
assert len(result) == 3
assert result[2] == -1
assert result[0].shape == (5, binode.input_dim)
assert not n.any(result[0])
def test_flow_from_sum(self):
"""Test the special addition method for BiNode."""
node1 = IdentityBiNode()
node2 = mdp.Node()
flow = node1 + node2
assert type(flow) is BiFlow
node2 = IdentityBiNode()
flow = node1 + node2
assert type(flow) is BiFlow
assert len(flow) == 2
node3 = IdentityBiNode()
flow = node1 + node2 + node3
assert type(flow) is BiFlow
assert len(flow) == 3
node4 = IdentityBiNode()
flow = node4 + flow
assert type(flow) is BiFlow
assert len(flow) == 4
class TestBiClassifierNode(object):
def test_biclassifier(self):
"""Test the BiClassifier base class."""
class TestBiClassifier(BiClassifier):
def _label(self, x):
return "LABELS"
def _prob(self, x):
return "PROPS"
@staticmethod
def is_trainable():
return False
node = TestBiClassifier()
x = n.empty((5,2))
msg = {"return_labels": "test->",
"return_probs": True}
result = node.execute(x, msg)
assert result[0] is x
assert "labels" not in result[1]
assert result[1]["probs"] == "PROPS"
assert result[1][msg["return_labels"] + "labels"] == "LABELS"
assert "rank" not in result[1]
msg = {"return_labels": None}
result = node.execute(x,msg)
assert result[0] is x
assert "labels" not in result[1]
assert "prop" not in result[1]
assert "rank" not in result[1]
def test_autogen_biclassifier(self):
"""Test that the autogenerated classifiers work."""
node = SignumBiClassifier()
msg = {"return_labels": True}
# taken from the SignumClassifier unittest
x = n.array([[1, 2, -3, -4], [1, 2, 3, 4]])
result = node.execute(x, msg)
assert result[0] is x
assert result[1]["labels"].tolist() == [-1, 1]
class TestIdentityBiNode(object):
def test_idnode(self):
"""Test the IdentityBiNode.
Instantiation is tested and it should perform like an id node, but
accept msg arguments.
"""
binode = IdentityBiNode(node_id="testing binode")
x = n.random.random((10,5))
msg = {"some array": n.random.random((10,3))}
# see if msg causes no problem
y, msg = binode.execute(x, msg)
assert n.all(x==y)
# see if missing msg causes problem
y = binode.execute(x)
assert n.all(x==y)
class TestJumpBiNode(object):
def test_node(self):
"""Test the JumpBiNode."""
train_results = [[(0, "t1")], [None], [(3, "t3")]]
stop_train_results = [None, (5, "st2"), (6, "st3")]
execute_results = [(None, {}), None, (None, {}, "et4")]
jumpnode = JumpBiNode(train_results=train_results,
stop_train_results=stop_train_results,
execute_results=execute_results)
x = n.random.random((2,2))
assert jumpnode.is_trainable()
# training
rec_train_results = []
rec_stop_train_results = []
for _ in range(len(train_results)):
rec_train_results.append([jumpnode.train(x)])
jumpnode.bi_reset()
rec_stop_train_results.append(jumpnode.stop_training())
jumpnode.bi_reset()
assert not jumpnode.is_training()
assert rec_train_results == train_results
assert rec_stop_train_results == rec_stop_train_results
# execution
rec_execute_results = []
for _ in range(4): # note that this is more then the execute_targets
rec_execute_results.append(jumpnode.execute(x))
execute_results[1] = x
execute_results.append(x)
assert (rec_execute_results == execute_results)
assert jumpnode.loop_counter == 4
class TestBiNodeCoroutine(object):
"""Test the coroutine decorator and the related BiNode functionality."""
def test_codecorator(self):
"""Test basic codecorator functionality."""
class CoroutineBiNode(BiNode):
@staticmethod
def is_trainable():
return False
@binode_coroutine(["alpha", "beta"])
def _execute(self, x, alpha):
"""Blabla."""
x, alpha, beta = yield (x, {"alpha": alpha, "beta": 2},
self.node_id)
x, alpha, beta = yield (x, {"alpha": alpha+1, "beta": beta+2},
self.node_id)
yield x, {"alpha": alpha, "beta": beta}
node = CoroutineBiNode(node_id="conode")
flow = BiFlow([node])
x = n.random.random((3,2))
y, msg = flow.execute(x, {"alpha": 3})
assert msg["alpha"] == 4
assert msg["beta"] == 4
assert node.execute.__doc__ == """Blabla."""
def test_codecorator2(self):
"""Test codecorator functionality with StopIteration."""
class CoroutineBiNode(BiNode):
@staticmethod
def is_trainable():
return False
@binode_coroutine(["alpha", "beta"])
def _execute(self, x, alpha):
x, alpha, beta = yield (x, {"alpha": alpha, "beta": 2},
self.node_id)
x, alpha, beta = yield (x, {"alpha": alpha+1, "beta": beta+2},
self.node_id)
raise StopIteration(x, {"alpha": alpha, "beta": beta})
node = CoroutineBiNode(node_id="conode")
flow = BiFlow([node])
x = n.random.random((3,2))
y, msg = flow.execute(x, {"alpha": 3})
assert msg["alpha"] == 4
assert msg["beta"] == 4
def test_codecorator_defaults(self):
"""Test codecorator argument default values."""
class CoroutineBiNode(BiNode):
@staticmethod
def is_trainable():
return False
@binode_coroutine(["alpha", "beta"], defaults=(7,8))
def _execute(self, x):
x, alpha, beta = yield (x, None, self.node_id)
raise StopIteration(x, {"alpha": alpha, "beta": beta})
node = CoroutineBiNode(node_id="conode")
flow = BiFlow([node])
x = n.random.random((3,2))
y, msg = flow.execute(x)
assert msg["alpha"] == 7
assert msg["beta"] == 8
def test_codecorator_no_iteration(self):
"""Test codecorator corner case with no iterations."""
class CoroutineBiNode(BiNode):
@staticmethod
def is_trainable():
return False
@binode_coroutine()
def _execute(self, x):
# at least one yield must be in a coroutine
if False:
yield None
raise StopIteration(None, {"a": 1}, self.node_id)
node1 = CoroutineBiNode()
x = n.random.random((3,2))
result = node1.execute(x)
assert result == (None, {"a": 1}, None)
def test_codecorator_reset1(self):
"""Test that codecorator correctly resets after termination."""
class CoroutineBiNode(BiNode):
@staticmethod
def is_trainable():
return False
@binode_coroutine()
def _execute(self, x, a, msg=None):
# note that the a argument is required, drop message
for _ in range(2):
x = yield x
raise StopIteration(x)
node1 = CoroutineBiNode()
x = n.random.random((3,2))
# this inits the coroutine, a argument is needed
node1.execute(x, {"a": 2})
node1.execute(x)
node1.execute(x)
assert node1._coroutine_instances == {}
# couroutine should be reset, a argument is needed again
py.test.raises(TypeError, node1.execute, x)
def test_codecorator_reset2(self):
"""Test that codecorator correctly resets without yields."""
class CoroutineBiNode(BiNode):
@staticmethod
def is_trainable():
return False
@binode_coroutine()
def _execute(self, x, a, msg=None):
if False:
yield
raise StopIteration(x)
node1 = CoroutineBiNode()
x = n.random.random((3,2))
node1.execute(x, {"a": 2})
assert node1._coroutine_instances == {}
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