def generate_conns(self):
"""Generate the set of direct Connections replacing this Cluster."""
outputs = {}
for c in self.conns_in | self.conns_mid | self.conns_out:
pre = c.pre_obj
if pre not in outputs:
outputs[pre] = set([c])
else:
outputs[pre].add(c)
for c in self.conns_in:
assert c.post_obj in self.objs
for k, (pre_slice, transform, synapse,
post) in enumerate(self.generate_from(c.post_obj,
outputs)):
syn = self.merge_synapses(c.synapse, synapse)
trans = self.merge_transforms(c.post_obj,
[c.size_mid, post.size_in],
[c.transform, transform],
[c.post_slice, pre_slice])
if not np.allclose(transform_array(trans), 0):
yield Connection(
pre=c.pre,
post=post,
function=c.function,
eval_points=c.eval_points,
scale_eval_points=c.scale_eval_points,
synapse=syn,
transform=trans,
add_to_container=False,
label=(None if c.label is None else "%s_%d" %
(c.label, k)),
)
def test_full_array(n_ensembles, ens_dimensions):
with nengo.Network() as model:
a = nengo.networks.EnsembleArray(10, n_ensembles, ens_dimensions)
b = nengo.networks.EnsembleArray(10, n_ensembles, ens_dimensions)
D = n_ensembles * ens_dimensions
nengo.Connection(a.output, b.input, transform=np.ones((D, D)))
split = PassthroughSplit(model)
assert len(split.to_add) == n_ensembles**2
pairs = set()
for conn in split.to_add:
assert conn.pre in a.all_ensembles
assert conn.post in b.all_ensembles
assert np.allclose(transform_array(conn.transform),
np.ones((ens_dimensions, ens_dimensions)))
pairs.add((conn.pre, conn.post))
assert len(pairs) == n_ensembles**2
def test_transform_merging(d1, d2, d3):
with nengo.Network() as model:
a = nengo.Ensemble(10, d1)
b = nengo.Node(None, size_in=d2)
c = nengo.Ensemble(10, d3)
t1 = np.random.uniform(-1, 1, (d2, d1))
t2 = np.random.uniform(-1, 1, (d3, d2))
conn_ab = nengo.Connection(a, b, transform=t1)
conn_bc = nengo.Connection(b, c, transform=t2)
split = PassthroughSplit(model)
assert split.to_remove == {b, conn_ab, conn_bc}
assert len(split.to_add) == 1
conn = next(iter(split.to_add))
assert np.allclose(transform_array(conn.transform), np.dot(t2, t1))
def test_identity_array(n_ensembles, ens_dimensions):
with nengo.Network() as model:
a = nengo.networks.EnsembleArray(10, n_ensembles, ens_dimensions)
b = nengo.networks.EnsembleArray(10, n_ensembles, ens_dimensions)
nengo.Connection(a.output, b.input)
split = PassthroughSplit(model)
assert len(split.to_add) == n_ensembles
pre = set()
post = set()
for conn in split.to_add:
assert conn.pre in a.all_ensembles or conn.pre_obj is a.input
assert conn.post in b.all_ensembles
assert np.allclose(transform_array(conn.transform),
np.eye(ens_dimensions))
pre.add(conn.pre)
post.add(conn.post)
assert len(pre) == n_ensembles
assert len(post) == n_ensembles
def format_transform(size, transform):
if is_transform_type(transform, "NoTransform"):
transform = np.array(1.0)
elif is_transform_type(transform, "Dense"):
transform = transform_array(transform)
else:
raise NotImplementedError(
"Mergeable transforms must be Dense; "
"set remove_passthrough=False")
if not isinstance(transform, np.ndarray):
raise NotImplementedError(
"Mergeable transforms must be specified as Numpy arrays, "
"not distributions. Set `remove_passthrough=False`.")
if transform.ndim == 0: # scalar
transform = np.eye(size) * transform
elif transform.ndim != 2:
raise BuildError("Unhandled transform shape: %s" %
(transform.shape, ))
return transform