def test_incorporate_engine():
engine = Engine(
T[:,:2],
cctypes=CCTYPES[:2],
distargs=DISTARGS[:2],
num_states=4,
rng=gu.gen_rng(0),
)
engine.transition(N=5)
# Incorporate a new dim into with a non-contiguous output.
engine.incorporate_dim(
T[:,2],
outputs=[10],
cctype=CCTYPES[2],
distargs=DISTARGS[2]
)
engine.transition(N=2)
# Serialize the engine, and run a targeted transtion on variable 10.
m = engine.to_metadata()
engine2 = Engine.from_metadata(m)
engine2.transition(N=2, cols=[10], multiprocess=0)
assert all(s.outputs == [0,1,10] for s in engine.states)
def test_lovecat_transition_columns():
"""Test transition_lovecat targeting specific rows and columns."""
D = generate_dataset_2()
# Create engine and place each variable in its own view.
engine = Engine(
D,
outputs=[
3,
2,
1,
0,
],
cctypes=['normal'] * D.shape[1],
Zv={
3: 0,
2: 1,
1: 2,
0: 3
},
multiprocess=1,
num_states=4,
rng=gu.gen_rng(2),
)
# Confirm all variables in singleton views.
for s in engine.states:
for a, b in itertools.combinations(s.outputs, 2):
assert s.Zv(a) != s.Zv(b)
# Store the row partition assignments of each variable.
Zr_saved = [{
var: sorted(s.view_for(var).Zr().items())
for var in s.outputs
} for s in engine.states]
# Transition only the column hyperparameters of outputs 2 and 3 should not alter
# the structure of either row or column partitions.
engine.transition_lovecat(
N=100,
cols=[
2,
3,
],
kernels=['column_hyperparameters'],
progress=False,
)
for i, s in enumerate(engine.states):
for a, b in itertools.combinations(s.outputs, 2):
assert s.Zv(a) != s.Zv(b)
assert all(
sorted(s.view_for(var).Zr().items()) == Zr_saved[i][var]
for var in s.outputs)
# Transition variables 2 and 3 should place them in the same view, without
# altering the view of variables 0 and 1.
engine.transition_lovecat(N=100, cols=[
2,
3,
])
for s in engine.states:
assert s.Zv(3) == s.Zv(2)
assert s.Zv(1) != s.Zv(0)
# Transition only row assignments of outputs 0 and 1 should not alter the
# view partition.
engine.transition_lovecat(
N=100,
cols=[
0,
1,
],
kernels=['row_partition_assignments'],
checkpoint=2,
)
for s in engine.states:
assert s.Zv(3) == s.Zv(2)
assert s.Zv(1) != s.Zv(0)
# Transition variables 0 and 1 should put them in the same view.
engine.transition_lovecat(
N=100,
cols=[
0,
1,
],
)
for s in engine.states:
assert s.Zv(3) == s.Zv(2)
assert s.Zv(1) == s.Zv(0)
# Add a new column 19 which is sum of 2 and 3, and place it in a singleton
# view.
T19 = D[:, 0] + D[:, 1]
engine.incorporate_dim(T19, [19], cctype='normal', v=125)
for s in engine.states:
assert s.Zv(19) == 125
# Transition all variables except 19 should not influence its view
# assignment.
engine.transition_lovecat(
N=10,
cols=[
3,
2,
0,
1,
],
checkpoint=2,
)
for s in engine.states:
assert all(s.Zv(19) != s.Zv(o) for o in s.outputs if o != 19)
# Transition only 19 should place it in the same views as 3 and 2.
engine.transition_lovecat(
N=100,
cols=[19],
)
for s in engine.states:
assert s.Zv(19) == s.Zv(3) == s.Zv(2)
