def test_d_get_set():
class TestClass:
pass
obj = TestClass()
obj.attr0 = TestClass()
obj.attr0.attr1 = "test"
assert d_get(obj, obfuscate("attr0"), obfuscate("attr1")) == "test"
# error if trying to set a new attribute
with pytest.raises(AssertionError):
d_set(obj, obfuscate("attr0"), obfuscate("attr2"), val="test2")
obj.attr0.attr2 = None
d_set(obj, obfuscate("attr0"), obfuscate("attr2"), val="test2")
assert obj.attr0.attr2 == "test2"
def test_interface_connection_errors(Simulator):
with nengo.Network() as net:
nengo.Ensemble(2, 1)
# test unbuilt model error
with Simulator(net) as sim:
sim.sims['loihi'].nxsdk_board = None
with pytest.raises(SimulationError, match="build.*before running"):
sim.step()
# test failed connection error
def start(*args, **kwargs):
raise Exception("Mock failure to connect")
with Simulator(net) as sim:
interface = sim.sims['loihi']
d_set(interface.nxsdk_board, b'c3RhcnQ=', val=start)
with pytest.raises(SimulationError, match="[Cc]ould not connect"):
interface.connect(attempts=1)
def build_core(nxsdk_core, core, seed=None): # noqa: C901
assert len(core.compartment_cfgs) < MAX_COMPARTMENT_CFGS
assert len(core.vth_cfgs) < MAX_VTH_CFGS
logger.debug("- Configuring compartments")
for i, cfg in enumerate(core.compartment_cfgs):
d_func(
d_get(nxsdk_core, b"Y3hQcm9maWxlQ2Zn")[i],
b"Y29uZmlndXJl",
kwargs={
b"ZGVjYXlW": cfg.decay_v,
b"ZGVjYXlV": cfg.decay_u,
b"cmVmcmFjdERlbGF5": cfg.refract_delay,
b"ZW5hYmxlTm9pc2U=": cfg.enable_noise,
b"YmFwQWN0aW9u": 1,
},
)
logger.debug("- Configuring vth_cfgs")
for i, cfg in enumerate(core.vth_cfgs):
d_func(
d_get(nxsdk_core, b"dnRoUHJvZmlsZUNmZw==")[i],
b"c3RhdGljQ2Zn",
b"Y29uZmlndXJl",
kwargs={b"dnRo": cfg.vth},
)
logger.debug("- Configuring synapse_cfgs")
for i, cfg in enumerate(core.synapse_cfgs):
if cfg is None:
continue
obj = d_get(nxsdk_core, b"c3luYXBzZUZtdA==")[i]
d_set(obj, b"d2d0TGltaXRNYW50", val=cfg.weight_limit_mant)
d_set(obj, b"d2d0TGltaXRFeHA=", val=cfg.weight_limit_exp)
d_set(obj, b"d2d0RXhw", val=cfg.weight_exp)
d_set(obj, b"ZGlzY01heFdndA==", val=cfg.disc_max_weight)
d_set(obj, b"bGVhcm5pbmdDZmc=", val=cfg.learning_cfg)
d_set(obj, b"dGFnQml0cw==", val=cfg.tag_bits)
d_set(obj, b"ZGx5Qml0cw==", val=cfg.delay_bits)
d_set(obj, b"d2d0Qml0cw==", val=cfg.weight_bits)
d_set(obj, b"cmV1c2VTeW5EYXRh", val=cfg.reuse_synapse_data)
d_set(obj, b"bnVtU3luYXBzZXM=", val=cfg.n_synapses)
d_set(obj, b"Y0lkeE9mZnNldA==", val=cfg.idx_offset)
d_set(obj, b"Y0lkeE11bHQ=", val=cfg.idx_mult)
d_set(obj, b"c2tpcEJpdHM=", val=cfg.skip_bits)
d_set(obj, b"aWR4Qml0cw==", val=cfg.idx_bits)
d_set(obj, b"c3luVHlwZQ==", val=cfg.synapse_type)
d_set(obj, b"ZmFub3V0VHlwZQ==", val=cfg.fanout_type)
d_set(obj, b"Y29tcHJlc3Npb24=", val=cfg.compression)
d_set(obj, b"c3RkcFByb2ZpbGU=", val=cfg.stdp_cfg)
d_set(obj, b"aWdub3JlRGx5", val=cfg.ignore_delay)
logger.debug("- Configuring stdp_pre_cfgs")
for i, trace_cfg in enumerate(core.stdp_pre_cfgs):
tcg = TraceConfigGenerator()
tc = d_func(
tcg,
b"Z2VuVHJhY2VDZmc=",
kwargs={
b"dGF1": trace_cfg.tau,
b"c3Bpa2VMZXZlbEludA==": trace_cfg.spike_int,
b"c3Bpa2VMZXZlbEZyYWM=": trace_cfg.spike_frac,
},
)
d_get(tc, b"d3JpdGVUb1JlZ2lzdGVy")(d_get(nxsdk_core, b"c3RkcFByZUNmZw==")[i])
# --- seed randomness
def seed_trace(trace_random, rng):
trace_random.random0 = rng.randint(2 ** 32)
trace_random.random1 = rng.randint(2 ** 32)
trace_random.random2 = rng.randint(2 ** 32)
rng = np.random.RandomState(seed)
# neuron noise
# TODO: how to set neuron noise?
# d_set (nxsdk_core, b'ZGVuZHJpdGVSYW5kb20=', b'd29yZA==',
# val=rng.randint(2 ** 32))
# pre trace rounding
seed_trace(d_get(nxsdk_core, b"c3RkcFByZVJhbmRvbQ=="), rng)
# post trace rounding
seed_trace(d_get(nxsdk_core, b"c3RkcFBvc3RSYW5kb20="), rng)
# soma activity trace rounding
seed_trace(d_get(nxsdk_core, b"c29tYVJhbmRvbQ=="), rng)
# synaptic rounding
d_set(
nxsdk_core,
b"c3luYXBzZVJlcGFja1JhbmRvbQ==",
b"d29yZA==",
val=rng.randint(2 ** 32),
)
# --- learning
first_learning_index = None
for synapse in core.iterate_synapses():
if synapse.learning and first_learning_index is None:
first_learning_index = core.synapse_axons[synapse][0]
core.learning_coreid = d_get(nxsdk_core, b"aWQ=")
break
num_stdp = 0
if first_learning_index is not None:
for synapse in core.iterate_synapses():
assert (
synapse.learning
), "Currently, all synapses on core are learning or none are"
axons = np.array(core.synapse_axons[synapse])
if synapse.learning:
num_stdp += len(axons)
assert np.all(axons >= first_learning_index)
if num_stdp > 0:
logger.debug("- Configuring PES learning")
# add configurations tailored to PES learning
d_func(
nxsdk_core,
b"c3RkcENmZw==",
b"Y29uZmlndXJl",
kwargs={
b"Zmlyc3RMZWFybmluZ0luZGV4": first_learning_index,
b"bnVtUmV3YXJkQXhvbnM=": 0,
},
)
assert core.stdp_pre_cfg_idx is None
assert core.stdp_cfg_idx is None
core.stdp_pre_cfg_idx = 0 # hard-code for now
core.stdp_cfg_idx = 0 # hard-code for now (also in synapse_cfg)
d_func(
d_get(nxsdk_core, b"c3RkcFByZVByb2ZpbGVDZmc=")[0],
b"Y29uZmlndXJl",
kwargs={
b"dXBkYXRlQWx3YXlz": 1,
b"bnVtVHJhY2Vz": 0,
b"bnVtVHJhY2VIaXN0": 0,
b"c3RkcFByb2ZpbGU=": 0,
},
)
# stdp config for positive error
d_func(
d_get(nxsdk_core, b"c3RkcFByb2ZpbGVDZmc=")[0],
b"Y29uZmlndXJl",
kwargs={
b"dUNvZGVQdHI=": 0,
b"ZGVjaW1hdGVFeHA=": 0,
b"bnVtUHJvZHVjdHM=": 1,
b"cmVxdWlyZVk=": 1,
b"dXNlc1hlcG9jaA==": 1,
},
)
# Microcode for the learning rule. `u1` evaluates the learning rule
# every 2**1 timesteps, `x1` is the pre-trace, `y1` is the post-trace,
# and 2^-7 is the learning rate.
ucode = d_get(micro_gen, b"cnVsZVRvVUNvZGU=")(
[d(b"ZHcgPSB1MSp4MSp5MSooMl4tNyk=")], **{d(b"ZG9PcHRpbWl6ZQ=="): False}
)
assert d_get(ucode, b"bnVtVUNvZGVz") == 1
d_set(
d_get(nxsdk_core, b"c3RkcFVjb2RlTWVt")[0],
b"d29yZA==",
val=d_get(ucode, b"dUNvZGVz")[0],
)
# stdp config for negative error
d_func(
d_get(nxsdk_core, b"c3RkcFByb2ZpbGVDZmc=")[1],
b"Y29uZmlndXJl",
kwargs={
b"dUNvZGVQdHI=": 1,
b"ZGVjaW1hdGVFeHA=": 0,
b"bnVtUHJvZHVjdHM=": 1,
b"cmVxdWlyZVk=": 1,
b"dXNlc1hlcG9jaA==": 1,
},
)
# use negative version of above microcode rule
ucode = d_get(micro_gen, b"cnVsZVRvVUNvZGU=")(
[d(b"ZHcgPSAtdTEqeDEqeTEqKDJeLTcp")], **{d(b"ZG9PcHRpbWl6ZQ=="): False}
)
assert d_get(ucode, b"bnVtVUNvZGVz") == 1
d_set(
d_get(nxsdk_core, b"c3RkcFVjb2RlTWVt")[1],
b"d29yZA==",
val=d_get(ucode, b"dUNvZGVz")[0],
)
tcg = TraceConfigGenerator()
tc = d_func(
tcg,
b"Z2VuVHJhY2VDZmc=",
kwargs={b"dGF1": 0, b"c3Bpa2VMZXZlbEludA==": 0, b"c3Bpa2VMZXZlbEZyYWM=": 0},
)
d_get(tc, b"d3JpdGVUb1JlZ2lzdGVy")(d_get(nxsdk_core, b"c3RkcFBvc3RDZmc=")[0])
# TODO: allocator should be checking that vmin, vmax are the same
# for all blocks on a core
n_compartments = 0
if len(core.blocks) > 0:
block0 = core.blocks[0]
vmin, vmax = block0.compartment.vmin, block0.compartment.vmax
assert all(block.compartment.vmin == vmin for block in core.blocks)
assert all(block.compartment.vmax == vmax for block in core.blocks)
neg_limit = np.log2(-vmin + 1)
pos_limit = (np.log2(vmax + 1) - 9) * 0.5
assert int(neg_limit) == neg_limit
assert int(pos_limit) == pos_limit
noise_exp = block0.compartment.noise_exp
noise_offset = block0.compartment.noise_offset
noise_at_membrane = block0.compartment.noise_at_membrane
assert all(block.compartment.noise_exp == noise_exp for block in core.blocks)
assert all(
block.compartment.noise_offset == noise_offset for block in core.blocks
)
assert all(
block.compartment.noise_at_membrane == noise_at_membrane
for block in core.blocks
)
if noise_exp < d(b"Nw==", int):
# unexpected shifting: exp less than threshold acts as exp + 1
noise_exp = noise_exp - 1
d_func(
nxsdk_core,
b"ZGVuZHJpdGVTaGFyZWRDZmc=",
b"Y29uZmlndXJl",
kwargs={
b"cG9zVm1MaW1pdA==": int(pos_limit),
b"bmVnVm1MaW1pdA==": int(neg_limit),
b"bm9pc2VFeHAw": noise_exp,
b"bm9pc2VNYW50T2Zmc2V0MA==": noise_offset,
b"bm9pc2VBdERlbmRPclZt": noise_at_membrane,
},
)
d_func(
nxsdk_core,
b"ZGVuZHJpdGVBY2N1bUNmZw==",
b"Y29uZmlndXJl",
kwargs={b"ZGVsYXlCaXRz": 3},
)
for block, compartment_idxs, ax_range in core.iterate_blocks():
build_block(nxsdk_core, core, block, compartment_idxs, ax_range)
n_compartments = max(max(compartment_idxs) + 1, n_compartments)
logger.debug("- Configuring n_updates=%d", ceil_div(n_compartments, 4))
d_func(
nxsdk_core,
b"bnVtVXBkYXRlcw==",
b"Y29uZmlndXJl",
kwargs={
b"bnVtVXBkYXRlcw==": ceil_div(n_compartments, 4),
b"bnVtU3RkcA==": num_stdp,
},
)
d_set(d_get(nxsdk_core, b"ZGVuZHJpdGVUaW1lU3RhdGU=")[0], b"dGVwb2No", val=2)
d_set(d_get(nxsdk_core, b"dGltZVN0YXRl")[0], b"dGVwb2No", val=2)
if src != dst:
print("=== SOURCE: %s" % (cFilePath, ))
print(src)
print("\n=== DEST: %s" % (tmp_path, ))
print(dst)
raise ValueError("Snip file not copied correctly")
# Also copy all the include files
include_path = os.path.join(tmp.name, name, "include")
shutil.copytree(includeDir, include_path)
assert os.path.isdir(include_path), "Copy failed %s" % include_path
return super().createProcess(name, tmp_path, include_path, *args,
**kwargs)
d_set(snip_maker, b"R3JhcGg=", val=SnipMaker)
except ImportError:
HAS_NXSDK = False
nxsdk_dir = None
nxsdk_version = None
nxsdk = None
exception = sys.exc_info()[1]
def assert_nxsdk(exception=exception):
raise exception
if HAS_NXSDK:
micro_gen = d_import(
def build_synapse( # noqa C901
nxsdk_core, core, block, synapse, compartment_idxs):
axon_ids = core.synapse_axons[synapse]
synapse_cfg_idx = core.synapse_cfg_idxs[synapse]
stdp_pre_cfg_idx = core.stdp_pre_cfg_idxs[synapse]
atom_bits = synapse.atom_bits()
axon_bits = synapse.axon_bits()
atom_bits_extra = synapse.atom_bits_extra()
target_compartments = set()
synapse_map = {} # map weight_idx to (ptr, pop_size, len)
total_synapse_ptr = int(core.synapse_entries[synapse][0])
for axon_idx, axon_id in enumerate(axon_ids):
assert axon_id <= 2**axon_bits
weight_idx = int(synapse.axon_weight_idx(axon_idx))
base = synapse.axon_compartment_base(axon_idx)
if weight_idx not in synapse_map:
weights = synapse.weights[weight_idx]
indices = synapse.indices[weight_idx]
weights = weights // synapse.synapse_cfg.scale
assert weights.ndim == 2
assert weights.shape == indices.shape
assert np.all(weights <= 255) and np.all(
weights >= -256), str(weights)
n_atoms, n_compartments = weights.shape
synapse_map[weight_idx] = (total_synapse_ptr, n_atoms,
n_compartments)
for p in range(n_atoms):
for q in range(n_compartments):
compartment_idx = compartment_idxs[indices[p, q]]
d_func(d_get(nxsdk_core,
b'c3luYXBzZXM=')[total_synapse_ptr],
b'Y29uZmlndXJl',
kwargs={
b'Q0lkeA==': compartment_idx,
b'V2d0': weights[p, q],
b'c3luRm10SWQ=': synapse_cfg_idx,
b'THJuRW4=': int(synapse.learning),
})
target_compartments.add(compartment_idx)
total_synapse_ptr += 1
synapse_ptr, n_atoms, n_compartments = synapse_map[weight_idx]
assert n_atoms <= 2**atom_bits
if base is None:
# this is a dummy axon with no weights, so set n_compartments to 0
synapse_ptr = 0
n_compartments = 0
base = 0
else:
base = int(base)
assert base <= d(b'MjU2', int), "Currently limited by hardware"
d_set(d_get(nxsdk_core, b'c3luYXBzZU1hcA==')[axon_id],
b'c3luYXBzZVB0cg==',
val=synapse_ptr)
d_set(d_get(nxsdk_core, b'c3luYXBzZU1hcA==')[axon_id],
b'c3luYXBzZUxlbg==',
val=n_compartments)
if synapse.pop_type == 0: # discrete
assert n_atoms == 1
d_func(d_get(nxsdk_core, b'c3luYXBzZU1hcA==')[axon_id],
b'ZGlzY3JldGVNYXBFbnRyeQ==',
b'Y29uZmlndXJl',
kwargs={b'Y3hCYXNl': base})
elif synapse.pop_type == 16: # pop16
d_set(d_get(nxsdk_core, b'c3luYXBzZU1hcA==')[axon_id],
b'cG9wU2l6ZQ==',
val=n_atoms)
assert base % 4 == 0
d_func(d_get(nxsdk_core, b'c3luYXBzZU1hcA==')[axon_id],
b'cG9wdWxhdGlvbjE2TWFwRW50cnk=',
b'Y29uZmlndXJl',
kwargs={
b'Y3hCYXNl': base // 4,
b'YXRvbUJpdHM=': atom_bits_extra,
})
elif synapse.pop_type == 32: # pop32
d_set(d_get(nxsdk_core, b'c3luYXBzZU1hcA==')[axon_id],
b'cG9wU2l6ZQ==',
val=n_atoms)
d_func(d_get(nxsdk_core, b'c3luYXBzZU1hcA==')[axon_id],
b'cG9wdWxhdGlvbjMyTWFwRW50cnk=',
b'Y29uZmlndXJl',
kwargs={b'Y3hCYXNl': base})
else:
raise BuildError("Synapse: unrecognized pop_type: %s" %
(synapse.pop_type, ))
if synapse.learning:
assert core.stdp_pre_cfg_idx is not None
assert stdp_pre_cfg_idx is not None
d_func(d_get(nxsdk_core, b'c3luYXBzZU1hcA==')[axon_id + 1],
b'c2luZ2xlVHJhY2VFbnRyeQ==',
b'Y29uZmlndXJl',
kwargs={
b'cHJlUHJvZmlsZQ==': core.stdp_pre_cfg_idx,
b'dGNz': stdp_pre_cfg_idx,
})
assert total_synapse_ptr == core.synapse_entries[synapse][1], (
"Synapse pointer did not align with precomputed synapse length")
if synapse.learning:
assert core.stdp_cfg_idx is not None
for compartment in target_compartments:
# TODO: check that no compartment configured by multiple synapses
d_func(
d_get(nxsdk_core, b'c3RkcFBvc3RTdGF0ZQ==')[compartment],
b'Y29uZmlndXJl',
kwargs={
b'c3RkcFByb2ZpbGU=': core.stdp_cfg_idx,
b'dHJhY2VQcm9maWxl': 3 # TODO: why this value
})