def test_chip_learning_errors():
with nengo.Network() as net:
add_params(net)
a = nengo.Ensemble(100, 1)
b = nengo.Ensemble(100, 1)
net.config[b].on_chip = True
nengo.Connection(a, b, learning_rule_type=nengo.PES())
with pytest.raises(BuildError, match="Post ensemble"):
Split(net)
with nengo.Network() as net:
add_params(net)
a = nengo.Ensemble(100, 1)
b = nengo.Ensemble(100, 1)
error = nengo.Ensemble(100, 1)
net.config[error].on_chip = True
conn = nengo.Connection(a, b, learning_rule_type=nengo.PES())
nengo.Connection(error, conn.learning_rule)
with pytest.raises(BuildError, match="Pre ensemble"):
Split(net)
def test_place_internetwork_connections():
with nengo.Network() as net:
add_params(net)
offchip = nengo.Ensemble(10, 1)
net.config[offchip].on_chip = False
onchip = nengo.Ensemble(10, 1)
onon = nengo.Connection(onchip, onchip)
onoff = nengo.Connection(onchip, offchip)
offon = nengo.Connection(offchip, onchip)
offoff = nengo.Connection(offchip, offchip)
split = Split(net)
assert split.on_chip(onon.pre)
assert split.on_chip(onon.post)
assert split.on_chip(onoff.pre)
assert not split.on_chip(onoff.post)
assert not split.on_chip(offon.pre)
assert split.on_chip(offon.post)
assert not split.on_chip(offoff.pre)
assert not split.on_chip(offoff.post)
def test_sliced_passthrough_bug():
with nengo.Network() as model:
a = nengo.Ensemble(1, 1, label="a")
passthrough = nengo.Node(size_in=1, label="passthrough")
nengo.Connection(a, passthrough)
p = nengo.Probe(passthrough[0])
split = Split(model, remove_passthrough=True)
assert len(split.passthrough.to_add) == 0
assert len(split.passthrough.to_remove) == 0
assert split.on_chip(a)
assert not split.on_chip(passthrough)
assert not split.on_chip(p)
def test_split_remove_passthrough(remove_passthrough):
with nengo.Network() as net:
keep1 = nengo.Node(0, label="keep1")
keep2 = nengo.Node(lambda t, x: x, size_in=1, label="keep2")
keep3 = nengo.Node(size_in=1, label="keep3")
chip1 = nengo.Ensemble(10, 1, label="chip1")
discard1 = nengo.Node(size_in=1, label="discard1")
chip2 = nengo.Ensemble(10, 1, label="chip2")
discard2 = nengo.Node(size_in=1, label="discard2")
chip3 = nengo.Ensemble(10, 1, label="chip3")
keep4 = nengo.Node(size_in=1, label="keep4")
probe = nengo.Probe(keep4)
nengo.Connection(keep1, keep2)
nengo.Connection(keep2, keep3)
nengo.Connection(keep3, chip1)
conn1 = nengo.Connection(chip1, discard1)
conn2 = nengo.Connection(discard1, chip2)
conn3 = nengo.Connection(chip2, discard2)
conn4 = nengo.Connection(discard2, chip3)
nengo.Connection(chip3, keep4)
split = Split(net, remove_passthrough=remove_passthrough)
assert not split.on_chip(probe)
if remove_passthrough:
assert split.passthrough.to_remove == {
conn1,
conn2,
conn3,
conn4,
discard1,
discard2,
}
conns = list(split.passthrough.to_add)
assert len(conns) == 2
prepost = {(conn.pre, conn.post) for conn in conns}
assert prepost == {(chip1, chip2), (chip2, chip3)}
else:
assert split.passthrough.to_remove == set()
assert split.passthrough.to_add == set()
def test_precompute_host_to_learning_rule_unsupported():
with nengo.Network() as net:
pre = nengo.Ensemble(10, 1, label="pre")
post = nengo.Ensemble(10, 1, label="post")
nengo.Connection(pre, post, learning_rule_type=nengo.PES())
with pytest.raises(BuildError, match="learning rules"):
Split(net, precompute=True)
def test_split_precompute_loop_error():
with nengo.Network() as net:
node_offchip = nengo.Node(lambda t, x: x + 1, size_in=1, size_out=1)
ens_onchip = nengo.Ensemble(10, 1)
nengo.Connection(node_offchip, ens_onchip)
nengo.Connection(ens_onchip, node_offchip)
with pytest.raises(BuildError, match="Cannot precompute"):
Split(net, precompute=True)
def test_split_pre_from_host():
with nengo.Network() as net:
add_params(net)
pre_1 = nengo.Node(0, label="pre_1")
pre_2 = nengo.Ensemble(10, 1, label="pre_2")
pre_3 = nengo.Node(size_in=1, label="pre_3")
pre_4 = nengo.Ensemble(1, 1, label="pre_4")
pre_5 = nengo.Probe(pre_4)
onchip = nengo.Ensemble(1, 1, label="onchip")
post1 = nengo.Ensemble(10, 1, label="post1")
post2 = nengo.Node(size_in=1, label="post2")
post3 = nengo.Probe(post2, label="post3")
nengo.Connection(pre_1, pre_2)
nengo.Connection(pre_2, pre_3)
nengo.Connection(pre_3, pre_4)
nengo.Connection(pre_4.neurons, onchip)
nengo.Connection(onchip, post1)
nengo.Connection(post1, post2)
net.config[pre_2].on_chip = False
net.config[pre_4].on_chip = False
net.config[post1].on_chip = False
split = Split(net, precompute=True)
host_precomputable = {pre_1, pre_2, pre_3, pre_4, pre_5}
for obj in host_precomputable:
assert not split.on_chip(obj)
assert split.is_precomputable(obj)
host_nonprecomputable = {post1, post2, post3}
for obj in host_nonprecomputable:
assert not split.on_chip(obj)
assert not split.is_precomputable(obj)
assert split.on_chip(onchip)
assert not split.is_precomputable(onchip)
with pytest.raises(BuildError, match="not a part of the network"):
split.is_precomputable(
nengo.Node(0, add_to_container=False))
def test_split_host_to_learning_rule():
with nengo.Network() as net:
add_params(net)
pre = nengo.Ensemble(10, 1, label="pre")
post = nengo.Ensemble(10, 1, label="post")
err_onchip = nengo.Ensemble(10, 1, label="err_onchip")
err_offchip = nengo.Ensemble(10, 1, label="err_offchip")
net.config[err_offchip].on_chip = False
ens_conn = nengo.Connection(pre, post, learning_rule_type=nengo.PES())
neurons_conn = nengo.Connection(pre.neurons, post.neurons,
learning_rule_type=nengo.PES())
nengo.Connection(err_onchip, ens_conn.learning_rule)
nengo.Connection(
err_onchip, neurons_conn.learning_rule)
nengo.Connection(err_offchip, ens_conn.learning_rule)
nengo.Connection(
err_offchip, neurons_conn.learning_rule)
split = Split(net)
assert split.on_chip(pre)
assert not split.on_chip(post)
assert not split.on_chip(err_onchip)
assert not split.on_chip(err_offchip)
def test_precompute_remove_passthrough():
with nengo.Network() as net:
add_params(net)
host = nengo.Node(0, label="host")
onchip1 = nengo.Ensemble(1, 1, label="onchip1")
passthrough1 = nengo.Node(size_in=1, label="passthrough1")
onchip2 = nengo.Ensemble(1, 1, label="onchip2")
passthrough2 = nengo.Node(size_in=1, label="passthrough2")
onchip3 = nengo.Ensemble(1, 1, label="onchip3")
nengo.Connection(host, onchip1)
nengo.Connection(onchip1, passthrough1)
nengo.Connection(passthrough1, onchip2)
nengo.Connection(onchip2, passthrough2)
nengo.Connection(passthrough2, onchip3)
split = Split(net, precompute=True, remove_passthrough=True)
assert split.is_precomputable(host)
assert not split.on_chip(host)
for obj in (onchip1, passthrough1, onchip2, passthrough2, onchip3):
assert not split.is_precomputable(obj)
for obj in (onchip1, onchip2, onchip3):
assert split.on_chip(obj)
def test_place_probes():
with nengo.Network() as net:
add_params(net)
offchip1 = nengo.Node(0)
with nengo.Network():
onchip1 = nengo.Ensemble(10, 1)
offchip2 = nengo.Ensemble(10, 1)
net.config[offchip2].on_chip = False
onchip2 = nengo.Ensemble(10, 1)
nengo.Connection(onchip1, onchip2)
nengo.Connection(offchip1, offchip2)
offchip_probes = [
nengo.Probe(offchip1),
nengo.Probe(offchip2),
]
onchip_probes = [
nengo.Probe(onchip1),
nengo.Probe(onchip2),
]
split = Split(net)
assert split.on_chip(onchip1)
assert split.on_chip(onchip2)
assert not split.on_chip(offchip1)
assert not split.on_chip(offchip2)
assert not any(split.on_chip(p) for p in offchip_probes)
assert all(split.on_chip(p) for p in onchip_probes)
def build_network(model,
network,
precompute=None,
remove_passthrough=True,
discretize=True):
if model.toplevel is None:
# We don't set model.toplevel to network because `nengo_build_network`
# will do that and relies on it being `None` initially.
# Ensure seeds are identical to Nengo
# Note: This does nothing for nengo<=2.8.0, seeds will always be different
seed_network(network, seeds=model.seeds, seeded=model.seeded)
# Determine how to split the host into one, two or three models
model.split = Split(network,
precompute=precompute,
remove_passthrough=remove_passthrough)
# Delegate most of the network building to Nengo
nengo_build_network(model, network, progress=None)
if network is model.toplevel:
# Build the extra passthrough connections into the model
passthrough = model.split.passthrough
for conn in passthrough.to_add:
# Note: connections added by the passthrough splitter do not have seeds
model.seeds[conn] = None
model.seeded[conn] = False
model.build(conn)
# Split blocks into blocks that will fit on cores
block_map = split_model(model)
model.block_comp_map = {
new_block: comp_idxs
for old_block, new_blocks in block_map.items()
for new_block, comp_idxs in new_blocks.items()
}
if discretize:
discretize_model(model)
validate_model(model)
def test_place_nodes():
# all nodes go on the host
# ChipReceiveNodes and HostSendNodes are created later by the builder
with nengo.Network() as net:
offchip1 = nengo.Node(0)
with nengo.Network():
offchip2 = nengo.Node(np.sin)
ensemble = nengo.Ensemble(100, 1)
offchip3 = nengo.Node(size_in=1)
nengo.Connection(ensemble, offchip3)
with nengo.Network():
nowhere = nengo.Node(0)
split = Split(net)
assert not split.on_chip(offchip1)
assert not split.on_chip(offchip2)
assert not split.on_chip(offchip3)
with pytest.raises(BuildError, match="not a part of the network"):
split.on_chip(nowhere)
def test_place_ensembles():
# builder will move the learning stuff onto the host
with nengo.Network() as net:
add_params(net)
offchip = nengo.Ensemble(10, 1, label="offchip")
net.config[offchip].on_chip = False
direct = nengo.Ensemble(
1, 1, neuron_type=nengo.Direct(), label="direct")
with nengo.Network():
onchip = nengo.Ensemble(20, 1, label="onchip")
pre = nengo.Ensemble(10, 1, label="pre")
post = nengo.Ensemble(10, 1, label="post")
error = nengo.Ensemble(10, 1, label="error")
conn = nengo.Connection(pre, post, learning_rule_type=nengo.PES())
nengo.Connection(error, conn.learning_rule)
split = Split(net)
assert not split.on_chip(offchip)
assert not split.on_chip(direct)
assert split.on_chip(onchip)
assert split.on_chip(pre)
assert not split.on_chip(post)
assert not split.on_chip(error)
for obj in net.all_ensembles + net.all_nodes:
assert not split.is_precomputable(obj)
with pytest.raises(BuildError, match="Locations are only established"):
split.on_chip(conn)
def __init__( # noqa: C901
self,
network,
dt=0.001,
seed=None,
model=None,
precompute=False,
target=None,
progress_bar=None,
remove_passthrough=True,
hardware_options=None,
):
# initialize values used in __del__ and close() first
self.closed = True
self.precompute = precompute
self.network = network
self.sims = OrderedDict()
self._run_steps = None
hardware_options = {} if hardware_options is None else hardware_options
if progress_bar:
warnings.warn("nengo-loihi does not support progress bars")
if HAS_DL:
install_dl_builders()
if model is None:
# Call the builder to make a model
self.model = Model(dt=float(dt), label="%s, dt=%f" % (network, dt))
else:
assert isinstance(
model,
Model), ("model is not type 'nengo_loihi.builder.Model'")
self.model = model
assert self.model.dt == dt
if network is None:
raise ValidationError("network parameter must not be None",
attr="network")
config.add_params(network)
# ensure seeds are identical to nengo
# this has no effect for nengo<=2.8.0
seed_network(network, seeds=self.model.seeds, seeded=self.model.seeded)
# determine how to split the host into one, two or three models
self.model.split = Split(network,
precompute=precompute,
remove_passthrough=remove_passthrough)
# Build the network into the model
self.model.build(network)
# Build the extra passthrough connections into the model
passthrough = self.model.split.passthrough
for conn in passthrough.to_add:
# Note: connections added by the passthrough splitter do not
# respect seeds
self.model.seeds[conn] = None
self.model.seeded[conn] = False
self.model.build(conn)
if len(self.model.host_pre.params):
assert precompute
self.sims["host_pre"] = nengo.Simulator(network=None,
dt=self.dt,
model=self.model.host_pre,
progress_bar=False,
optimize=False)
elif precompute:
warnings.warn("No precomputable objects. Setting "
"precompute=True has no effect.")
if len(self.model.host.params):
self.sims["host"] = nengo.Simulator(network=None,
dt=self.dt,
model=self.model.host,
progress_bar=False,
optimize=False)
elif not precompute:
# If there is no host and precompute=False, then all objects
# must be on the chip, which is precomputable in the sense that
# no communication has to happen with the host.
# We could warn about this, but we want to avoid people having
# to specify `precompute` unless they absolutely have to.
self.precompute = True
self._probe_outputs = self.model.params
self.data = ProbeDict(self._probe_outputs)
for sim in self.sims.values():
self.data.add_fallback(sim.data)
if seed is None:
if network is not None and network.seed is not None:
seed = network.seed + 1
else:
seed = np.random.randint(npext.maxint)
if target is None:
target = 'loihi' if HAS_NXSDK else 'sim'
self.target = target
logger.info("Simulator target is %r", target)
logger.info("Simulator precompute is %r", self.precompute)
if target != "simreal":
discretize_model(self.model)
if target in ("simreal", "sim"):
self.sims["emulator"] = EmulatorInterface(self.model, seed=seed)
elif target == 'loihi':
assert HAS_NXSDK, "Must have NxSDK installed to use Loihi hardware"
self.sims["loihi"] = HardwareInterface(
self.model,
use_snips=not self.precompute,
seed=seed,
**hardware_options)
else:
raise ValidationError("Must be 'simreal', 'sim', or 'loihi'",
attr="target")
assert "emulator" in self.sims or "loihi" in self.sims
self.closed = False
self.reset(seed=seed)