def test_assembly(self):
size_a = random.randint(1, 1000)
size_b = random.randint(1, 1000)
pop_a = pyhmf.Population(size_a, pyhmf.IF_cond_exp)
pop_b = pyhmf.Population(size_b, pyhmf.IF_cond_exp)
pop_c = pyhmf.Population(1, pyhmf.IF_cond_exp)
view = pop_b[0:random.randint(1, size_b)]
text = '%ds till the end' % (size_a + size_b)
construction_styles = [
pyhmf.Assembly(pop_a, view, label=text),
pyhmf.Assembly([pop_a, view], label=text),
pyhmf.Assembly((pop_a, view), label=text)
]
for asm in construction_styles:
self.assertEqual(len(asm), len(list(asm.__iter__())))
self.assertEqual(len(asm), len(list(asm.all())))
self.assertEqual(size_a + len(view), len(asm))
self.assertEqual(size_a + len(view), asm.size)
self.assertEqual(text, asm.label)
# some more tests ;)
pyhmf.Assembly(pop_a),
pyhmf.Assembly(pop_a, label=text),
pyhmf.Assembly([pop_a]),
pyhmf.Assembly([pop_a], label=text),
pyhmf.Assembly(pop_c, label=text),
def test_projection_weights(self):
import numpy
from numpy.testing import assert_equal, assert_almost_equal, assert_array_equal
import pyhmf as pynn
size = (100, 300)
noC = size[0] * size[1]
p1, p2 = pynn.Population(size[0], pynn.EIF_cond_exp_isfa_ista), pynn.Population(size[1], pynn.EIF_cond_exp_isfa_ista)
prj1 = pynn.Projection(p1, p2, pynn.AllToAllConnector() )
prj1.setWeights(4.0)
assert_array_equal(numpy.ones(noC) * 4.0, prj1.getWeights())
assert_array_equal(numpy.ones(size) * 4.0, prj1.getWeights("matrix") )
prj1.setWeights( numpy.ones(noC) * 3.0 )
assert_array_equal(numpy.ones(noC) * 3.0, prj1.getWeights() )
assert_array_equal(numpy.ones(size) * 3.0, prj1.getWeights("matrix") )
prj1.setWeights( numpy.ones(size) * 2.0 )
assert_array_equal(numpy.ones(noC) * 2.0, prj1.getWeights() )
assert_array_equal(numpy.ones(size) * 2.0, prj1.getWeights("matrix") )
prj2 = pynn.Projection(p1, p2, pynn.AllToAllConnector(delays = 2.5, weights = numpy.ones(size)))
assert_array_equal(numpy.ones(noC) * 2.5, prj2.getDelays() )
assert_array_equal(numpy.ones(size) * 2.5, prj2.getDelays("matrix") )
assert_array_equal(numpy.ones(noC) * 1.0, prj2.getWeights() )
assert_array_equal(numpy.ones(size) * 1.0, prj2.getWeights("matrix") )
def test_issue2048(self):
if self.API_VERSION == "0.8":
def generate_spike_times(i_range):
return [
pyNN.parameters.Sequence(
numpy.add.accumulate(
numpy.random.exponential(10.0, size=10)))
for i in i_range
]
p = pyhmf.Population(
30, pyhmf.SpikeSourceArray(spike_times=generate_spike_times))
elif self.API_VERSION == "0.7":
def generate_spike_times(i_range):
return [
numpy.add.accumulate(
numpy.random.exponential(10.0, size=10))
for i in i_range
]
p = pyhmf.Population(
30, pyhmf.SpikeSourceArray,
{'spike_times': generate_spike_times(list(range(30)))})
def test_popview_on_hicann(self, size):
pynn.setup(marocco=self.marocco)
neuron_size = 4
self.marocco.neuron_placement.default_neuron_size(neuron_size)
hicann = C.HICANNOnWafer(Enum(122))
hicann_1 = C.HICANNOnWafer(Enum(123))
hicann_2 = C.HICANNOnWafer(Enum(124))
hicann_3 = C.HICANNOnWafer(Enum(125))
pop = pynn.Population(size, pynn.IF_cond_exp, {})
pop_1 = pynn.Population(size, pynn.IF_cond_exp, {})
pop_view = pynn.PopulationView(pop,list(range(0,size,2)))
pop_view_1 = pynn.PopulationView(pop,list(range(1,size,2)))
pop_1_view = pynn.PopulationView(pop_1,list(range(1,size//2)))
pop_1_view_1 = pynn.PopulationView(pop_1,list(range(size-2,size//2,-1)))
pop_auto_placement = pynn.PopulationView(pop_1,[0,size//2,size-1])
self.marocco.manual_placement.on_hicann(pop_view, hicann)
self.marocco.manual_placement.on_hicann(pop_view_1, hicann_1)
self.marocco.manual_placement.on_hicann(pop_1_view, hicann_2)
self.marocco.manual_placement.on_hicann(pop_1_view_1, hicann_3)
if neuron_size * size//2 > C.NeuronOnHICANN.enum_type.size:
with self.assertRaises(RuntimeError):
pynn.run(0)
pynn.end()
return
pynn.run(0)
pynn.end()
results = self.load_results()
for nrn in pop_view:
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
for denmem in logical_neuron:
self.assertEqual(hicann, denmem.toHICANNOnWafer())
for nrn in pop_view_1:
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
for denmem in logical_neuron:
self.assertEqual(hicann_1, denmem.toHICANNOnWafer())
for nrn in pop_1_view:
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
for denmem in logical_neuron:
self.assertEqual(hicann_2, denmem.toHICANNOnWafer())
for nrn in pop_1_view_1:
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
for denmem in logical_neuron:
self.assertEqual(hicann_3, denmem.toHICANNOnWafer())
for nrn in pop_auto_placement:
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
for denmem in logical_neuron:
self.assertIsNotNone(denmem.toHICANNOnWafer())
def test_issue2051(self):
p1 = pyhmf.Population(1000, pyhmf.EIF_cond_exp_isfa_ista)
p2 = pyhmf.Population(1000, pyhmf.EIF_cond_exp_isfa_ista)
if self.API_VERSION == "0.8":
prj = pyhmf.Projection(p1, p2, pyhmf.AllToAllConnector(),
pyhmf.StaticSynapse(weight=0.05, delay=0.5))
params = {
'U': 0.04,
'tau_rec': 100.0,
'tau_facil': 1000.0,
'weight': 0.01
}
facilitating = pyhmf.TsodyksMarkramSynapse(**params)
prj = pyhmf.Projection(
p1,
p2,
pyhmf.FixedProbabilityConnector(p_connect=0.1),
synapse_type=facilitating)
elif self.API_VERSION == "0.7":
prj = pyhmf.Projection(
p1, p2, pyhmf.AllToAllConnector(weights=0.05, delays=0.5))
params = {'U': 0.04, 'tau_rec': 100.0, 'tau_facil': 1000.0}
facilitating = pyhmf.SynapseDynamics(
fast=pyhmf.TsodyksMarkramMechanism(**params))
prj = pyhmf.Projection(p1,
p2,
pyhmf.FixedProbabilityConnector(
p_connect=0.1, weights=0.01),
synapse_dynamics=facilitating)
def test_issue2053(self):
p1 = pyhmf.Population(1000, pyhmf.EIF_cond_exp_isfa_ista)
p2 = pyhmf.Population(1000, pyhmf.EIF_cond_exp_isfa_ista)
rand_distr = numpy.zeros(1000)
if self.API_VERSION == "0.8":
prj = pyhmf.Projection(p1, p2, pyhmf.AllToAllConnector(),
pyhmf.StaticSynapse(weight=0.05, delay=0.5))
prj.get('weight', format='list', with_address=False)
prj.set(delay=rand_distr)
prj.set(tau_rec=50.0)
prj.save('weight', 'exc_weights.txt', format='array')
prj.save('all', 'exc_conn.txt', format='list')
weights, delays = prj.get(['weight', 'delay'], format='array')
prj.set(weight=rand_distr, delay=0.4)
elif self.API_VERSION == "0.7":
prj = pyhmf.Projection(
p1, p2, pyhmf.AllToAllConnector(weights=0.05, delays=0.5))
prj.getWeights(format='list')
prj.randomizeDelays(rand_distr)
prj.setSynapseDynamics('tau_rec', 50.0)
prj.printWeights('exc_weights.txt', format='array')
prj.saveConnections('exc_conn.txt')
weights, delays = prj.getWeights('array'), prj.getDelays('array')
prj.randomizeWeights(rand_distr)
prj.setDelays(0.4)
def test_with_size(self):
pynn.setup(marocco=self.marocco)
default_size = 4
self.marocco.neuron_placement.default_neuron_size(default_size)
sizes = {}
pop = pynn.Population(1, pynn.IF_cond_exp, {})
sizes[pop] = default_size
pop = pynn.Population(1, pynn.IF_cond_exp, {})
self.marocco.manual_placement.with_size(pop, 2)
sizes[pop] = 2
pop = pynn.Population(1, pynn.IF_cond_exp, {})
self.marocco.manual_placement.with_size(pop, 6)
sizes[pop] = 6
pynn.run(0)
pynn.end()
results = self.load_results()
for pop, size in sizes.items():
placement_item, = results.placement.find(pop[0])
logical_neuron = placement_item.logical_neuron()
self.assertEqual(size, logical_neuron.size())
def test(self):
import pyhmf as pynn
from pymarocco import PyMarocco
import pylogging, pyhalbe
pyhalbe.Debug.change_loglevel(2)
pylogging.set_loglevel(pylogging.get("marocco"),
pylogging.LogLevel.TRACE)
pylogging.set_loglevel(pylogging.get("sthal"),
pylogging.LogLevel.DEBUG)
marocco = PyMarocco()
marocco.neuron_placement.default_neuron_size(4)
pynn.setup(marocco=marocco)
neuron1 = pynn.Population(1, pynn.IF_cond_exp)
inh = pynn.Population(1, pynn.SpikeSourceArray, {'spike_times': [0]})
exc = pynn.Population(1, pynn.SpikeSourceArray, {'spike_times': [0]})
exc_2 = pynn.Population(1, pynn.SpikeSourceArray, {'spike_times': [0]})
exc_3 = pynn.Population(1, pynn.SpikeSourceArray, {'spike_times': [0]})
c_exc = pynn.FixedProbabilityConnector(p_connect=1.0, weights=1)
proj1 = pynn.Projection(inh, neuron1, c_exc, target='excitatory')
proj2 = pynn.Projection(exc, neuron1, c_exc, target='excitatory')
proj3 = pynn.Projection(exc_2, neuron1, c_exc, target='excitatory')
proj4 = pynn.Projection(exc_3, neuron1, c_exc, target='inhibitory')
pynn.run(10000)
pynn.end()
def build(self):
# Set the neurons
self.neuronsVisible = pynn.Population(self.Nvisible, self.model)
self.neuronsHidden = pynn.Population(self.Nhidden, self.model)
# in the fully connected rbm each neuron from the visible layer
# projects to each neuron of the hidden layer (and vice versa)
# both inhibitory and excitatory to enable switching the sing of the
# connection during eventual training
# self connections are excluded
# This model only sets the skeleton of the BM without the noise sources
connector = pynn.AllToAllConnector(weights=0.003,
allow_self_connections=False)
pynn.Projection(self.neuronsVisible,
self.neuronsHidden,
connector,
target='excitatory')
pynn.Projection(self.neuronsVisible,
self.neuronsHidden,
connector,
target='inhibitory')
pynn.Projection(self.neuronsHidden,
self.neuronsVisible,
connector,
target='excitatory')
pynn.Projection(self.neuronsHidden,
self.neuronsVisible,
connector,
target='inhibitory')
def test_get_denmems(self):
pop_size = 2
for neuron_size in [4, 8, 12, 16, 32]:
self.marocco.neuron_placement.default_neuron_size(neuron_size)
pynn.setup(marocco=self.marocco)
target = pynn.Population(pop_size, pynn.IF_cond_exp, {})
populations = [target]
for i in range(3):
p1 = pynn.Population(pop_size, pynn.SpikeSourceArray,
{'spike_times': [1.]})
p2 = pynn.Population(pop_size, pynn.IF_cond_exp, {})
pynn.Projection(p1, target,
pynn.OneToOneConnector(weights=0.004))
pynn.Projection(p2, target,
pynn.OneToOneConnector(weights=0.004))
populations.append(p2)
pynn.run(0)
pynn.end()
mapstats = self.marocco.getStats()
results = Marocco.from_file(self.marocco.persist)
for pop in populations:
for nrn in range(pop_size):
for item in results.placement.find(pop[nrn]):
self.assertFalse(item.logical_neuron().is_external())
self.assertEqual(neuron_size,
item.logical_neuron().size())
def build_network(num_pops, pop_size, marocco):
from pymarocco import PyMarocco
import pyhmf as pynn
logging.info("num_pops: %d, pop_size: %d, total size: %d" %
(num_pops, pop_size, num_pops * pop_size))
pynn.setup(marocco=marocco)
pops = [
pynn.Population(pop_size, pynn.EIF_cond_exp_isfa_ista)
for x in range(num_pops)
]
for idx, pop in enumerate(pops):
connector = pynn.AllToAllConnector(allow_self_connections=True,
weights=1.)
# build ring like network topology
pynn.Projection(pop,
pops[(idx + 1) % len(pops)],
connector,
target='excitatory')
# add poisson stimulus
source = pynn.Population(1, pynn.SpikeSourcePoisson, {'rate': 2})
pynn.Projection(source, pop, connector, target='excitatory')
pynn.run(1)
pynn.end()
stats = marocco.getStats()
loss = float(stats.getSynapseLoss()) / stats.getSynapses()
return (num_pops, pop_size, loss)
def test_min_spl1_should_allow_external_input_on_same_chip(self):
"""
Even when the rightmost neuron block / DNC merger is not reserved for external input, it
should be possible to place external input on the same chip.
"""
pynn.setup(marocco=self.marocco)
neuron_size = 4
self.marocco.neuron_placement.default_neuron_size(neuron_size)
self.marocco.merger_routing.strategy(
self.marocco.merger_routing.minimize_number_of_sending_repeaters)
# Do not reserve rightmost neuron block / DNC merger for external input.
self.marocco.neuron_placement.restrict_rightmost_neuron_blocks(False)
hicann = C.HICANNOnWafer(C.Enum(123))
pops = []
# All but the first neuron block are occupied.
for nb in range(1, C.NeuronBlockOnHICANN.end):
pop = pynn.Population(1, pynn.IF_cond_exp, {})
self.marocco.manual_placement.on_neuron_block(
pop, C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(nb), hicann))
pops.append(pop)
in_pop = pynn.Population(1, pynn.SpikeSourceArray, {})
self.marocco.manual_placement.on_hicann(in_pop, hicann)
pynn.run(0)
pynn.end()
results = self.load_results()
for pop in pops:
nrn = pop[0]
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
self.assertEqual(neuron_size, logical_neuron.size())
for denmem in logical_neuron:
self.assertEqual(hicann, denmem.toHICANNOnWafer())
address = placement_item.address()
# All used neuron blocks should be connected to a single DNC merger.
dnc = C.DNCMergerOnHICANN(3)
self.assertEqual(hicann, address.toHICANNOnWafer())
self.assertEqual(dnc, address.toDNCMergerOnHICANN())
self.assertEqual(C.DNCMergerOnWafer(dnc, hicann),
address.toDNCMergerOnWafer())
nrn = in_pop[0]
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
self.assertTrue(logical_neuron.is_external())
address = placement_item.address()
# External input should be on the leftmost DNC merger, since all other
# mergers do not have direct access to a background generator.
dnc = C.DNCMergerOnHICANN(0)
self.assertEqual(hicann, address.toHICANNOnWafer())
self.assertEqual(dnc, address.toDNCMergerOnHICANN())
self.assertEqual(C.DNCMergerOnWafer(dnc, hicann),
address.toDNCMergerOnWafer())
def test_L1_detour_at_side_switch_usage(self):
"""
[155]
191
[223] 224 225 x226x {227}
test detour and predecessor settings at the edge of a wafer
"""
pylogging.set_loglevel(pylogging.get("marocco"),
pylogging.LogLevel.TRACE)
pylogging.set_loglevel(pylogging.get("Calibtic"),
pylogging.LogLevel.ERROR)
self.marocco.persist = '' # or add test suite TestWithRuntime?
runtime = Runtime(self.marocco.default_wafer)
pynn.setup(marocco=self.marocco, marocco_runtime=runtime)
settings = pysthal.Settings.get()
settings.synapse_switches.max_switches_per_column_per_side = 1
settings.crossbar_switches.max_switches_per_row = 1
source = pynn.Population(1, pynn.IF_cond_exp, {})
target1 = pynn.Population(1, pynn.IF_cond_exp, {})
target2 = pynn.Population(1, pynn.IF_cond_exp, {})
proj = pynn.Projection(
source, target1, pynn.AllToAllConnector(weights=1.))
proj = pynn.Projection(
source, target2, pynn.AllToAllConnector(weights=1.))
source_hicann = C.HICANNOnWafer(Enum(227))
target1_hicann = C.HICANNOnWafer(Enum(155))
target2_hicann = C.HICANNOnWafer(Enum(225))
self.marocco.manual_placement.on_hicann(source, source_hicann)
self.marocco.manual_placement.on_hicann(target1, target1_hicann)
self.marocco.manual_placement.on_hicann(target2, target2_hicann)
disabled_hicanns = [226, 263]
wafer = self.marocco.default_wafer
self.marocco.defects.set(pyredman.Wafer(runtime.wafer().index()))
for hicann in C.iter_all(C.HICANNOnWafer):
if hicann.toEnum().value() in disabled_hicanns:
self.marocco.defects.wafer().hicanns().disable(C.HICANNGlobal(hicann, wafer))
continue
pynn.run(0)
pynn.end()
for hicann in runtime.wafer().getAllocatedHicannCoordinates():
h = runtime.wafer()[hicann]
print(hicann, h.check())
self.assertEqual(h.check(), "")
def test_projections(self):
pynn.setup(marocco=self.marocco)
target = pynn.Population(1, pynn.IF_cond_exp, {})
pop_a = pynn.Population(2, pynn.SpikeSourceArray,
{'spike_times': [1.]})
pop_b = pynn.Population(1, pynn.SpikeSourceArray,
{'spike_times': [2.]})
pop_ab = pynn.Assembly()
pop_ab += pop_a
pop_ab += pop_b
con = pynn.AllToAllConnector(weights=0.004)
proj_a = pynn.Projection(pop_a, target, con)
proj_b = pynn.Projection(pop_b, target, con)
proj_ab = pynn.Projection(pop_ab, target, con)
pynn.run(0)
pynn.end()
results = self.load_results()
synapses = results.synapse_routing.synapses()
items_a = synapses.find(proj_a)
self.assertEqual(2, len(items_a))
items_b = synapses.find(proj_b)
self.assertEqual(1, len(items_b))
items_ab = synapses.find(proj_ab)
self.assertEqual(3, len(items_ab))
def to_hw_synapses(items):
hw_synapses = set()
for item in items:
synapse = item.hardware_synapse()
if synapse:
hw_synapses.add(synapse)
return hw_synapses
hw_a = to_hw_synapses(items_a)
hw_b = to_hw_synapses(items_b)
hw_ab = to_hw_synapses(items_ab)
self.assertTrue(hw_a.isdisjoint(hw_b))
self.assertTrue(hw_a.isdisjoint(hw_ab))
self.assertTrue(hw_b.isdisjoint(hw_ab))
for source_neuron in pop_a:
items = synapses.find(proj_ab, source_neuron, target[0])
self.assertEqual(1, len(items))
self.assertTrue(hw_ab.issuperset(to_hw_synapses(items)))
for source_neuron in pop_b:
items = synapses.find(proj_ab, source_neuron, target[0])
self.assertEqual(1, len(items))
self.assertTrue(hw_ab.issuperset(to_hw_synapses(items)))
def test_issue2046(self):
if self.API_VERSION in ("0.7", "0.8"):
# PyNN 0.7 style, deprecated but still supported in 0.8
p = pyhmf.Population(1000, pyhmf.IF_cond_exp, {'tau_m': 12.0, 'cm': 0.8})
if self.API_VERSION == "0.8":
p = pyhmf.Population(1000, pyhmf.IF_cond_exp(**{'tau_m': 12.0, 'cm': 0.8}))
cell_type = pyhmf.IF_cond_exp(tau_m=12.0, cm=0.8)
p = pyhmf.Population(1000, cell_type)
def test_issue1565(self):
# although there is only 1 synapse column per neuron (of size 2), a 2nd synapse is used
self.marocco.neuron_placement.default_neuron_size(2)
con = pynn.FixedProbabilityConnector(p_connect=1.0, weights=0.004)
pynn.setup(marocco=self.marocco)
pop1 = pynn.Population(10, pynn.IF_cond_exp, {})
ipu1 = pynn.Population(2, pynn.SpikeSourceArray, {'spike_times': []})
pro1 = pynn.Projection(ipu1, pop1, con, target='excitatory')
pynn.run(0)
def test_min_spl1_is_nongreedy_when_pops_are_placed_to_nbs(self, nbs):
"""
See above. Instead of a single population placed to the HICANN, populations are placed to
specific neuron blocks.
"""
pynn.setup(marocco=self.marocco)
neuron_size = 4
self.marocco.neuron_placement.default_neuron_size(neuron_size)
self.marocco.merger_routing.strategy(
self.marocco.merger_routing.minimize_number_of_sending_repeaters)
self.marocco.neuron_placement.restrict_rightmost_neuron_blocks(True)
hicann = C.HICANNOnWafer(C.Enum(123))
pops = []
for nb in nbs:
pop = pynn.Population(1, pynn.IF_cond_exp, {})
self.marocco.manual_placement.on_neuron_block(
pop, C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(nb), hicann))
pops.append(pop)
in_pop = pynn.Population(1, pynn.SpikeSourceArray, {})
self.marocco.manual_placement.on_hicann(in_pop, hicann)
pynn.run(0)
pynn.end()
results = self.load_results()
for pop in pops:
nrn = pop[0]
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
self.assertEqual(neuron_size, logical_neuron.size())
for denmem in logical_neuron:
self.assertEqual(hicann, denmem.toHICANNOnWafer())
address = placement_item.address()
# All used neuron blocks should still be connected to a single DNC merger.
dnc = C.DNCMergerOnHICANN(3)
self.assertEqual(hicann, address.toHICANNOnWafer())
self.assertEqual(dnc, address.toDNCMergerOnHICANN())
self.assertEqual(C.DNCMergerOnWafer(dnc, hicann),
address.toDNCMergerOnWafer())
nrn = in_pop[0]
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
self.assertTrue(logical_neuron.is_external())
address = placement_item.address()
# External input should be on the rightmost DNC merger since that is tried first.
dnc = C.DNCMergerOnHICANN(7)
self.assertEqual(hicann, address.toHICANNOnWafer())
self.assertEqual(dnc, address.toDNCMergerOnHICANN())
self.assertEqual(C.DNCMergerOnWafer(dnc, hicann),
address.toDNCMergerOnWafer())
def test_TwoNeuron(self):
if True:
pynn.setup(marocco=self.marocco)
# create neuron with v_rest below v_thresh
source = pynn.Population(1, pynn.EIF_cond_exp_isfa_ista, {
'v_rest': -50.,
'v_thresh': -60.,
'v_reset': -70.6,
})
N = 8 # number of target populations
p = [
pynn.Population(1, pynn.EIF_cond_exp_isfa_ista)
for i in range(N)
]
# place source on HICANN 0
source_hicann = self.chip(0)
self.marocco.manual_placement.on_hicann(source, source_hicann)
# place targets on all HICANNs on same reticle but random neurons
nrns = self.shuffle(255)
for ii, pop in enumerate(p):
hicann = HICANNGlobal(X(int(source_hicann.x()) + ii % 4),
Y(int(source_hicann.y()) + ii // 4))
self.marocco.manual_placement.on_hicann(pop, hicann)
print(pop, hicann)
connector = pynn.AllToAllConnector(allow_self_connections=True,
weights=1.)
store = []
# connect source to targets
for trg in p:
proj = pynn.Projection(source,
trg,
connector,
target='excitatory')
weights = copy.deepcopy(proj.getWeights())
store.append((proj, weights))
# start simulation
pynn.run(10) # in ms
pynn.end()
# make sure we have no synapse loss
self.assertEqual(0, self.marocco.stats.getSynapseLoss())
# assert weights are the same (at least as long as we don't send be
# the transformed digital weights)
for proj, weights in store:
self.assertEqual(self.marocco.stats.getWeights(proj), weights)
def test_external_sources_projections(self, params):
nprojections = params[0]
nsources = params[1]
print((nprojections, nsources))
"""
An external sources has multiple projections
so it should be split if it wuld not be of size 1
so unfortunately the users would need to live with that.
"""
pylogging.set_loglevel(pylogging.get("marocco"),
pylogging.LogLevel.TRACE)
pylogging.set_loglevel(pylogging.get("Calibtic"),
pylogging.LogLevel.ERROR)
pynn.setup(marocco=self.marocco)
self.marocco.neuron_placement.default_neuron_size(4)
# ensure a limited synapse driver chain length.
self.marocco.synapse_routing.driver_chain_length(3)
# we expect synapse loss, but we dont care, as the source cant be split.
# we want this tests not to throw exceptions.
self.marocco.continue_despite_synapse_loss = True
target = pynn.Population(1, pynn.IF_cond_exp, {})
hicann = C.HICANNOnWafer(Enum(100))
self.marocco.manual_placement.on_hicann(target, hicann)
exsource = pynn.Population(nsources, pynn.SpikeSourcePoisson,
{'rate': 1.})
for i in range(nprojections):
proj = pynn.Projection(exsource, target,
pynn.AllToAllConnector(weights=1.))
# access to proj so flake8 keeps silent
proj.size
pynn.run(0)
pynn.end()
results = self.load_results()
synapses = results.synapse_routing.synapses()
placement = results.placement
for dnc in C.iter_all(C.DNCMergerOnWafer):
PonDNC = placement.find(dnc) # PopulationOnDNC
if PonDNC:
## if driver requirements exceeded, only one source should be
## placed on the DNC, but synapse loss is still expected
if (nprojections > 4): # this number is just guessed
self.assertTrue(len(PonDNC) <= 1)
else:
self.assertTrue(len(PonDNC) <= 12)
def test_loss_in_wafer_routing(self, mode):
h0 = HICANNGlobal(HICANNOnWafer(Enum(0)), Wafer(33))
h1 = HICANNGlobal(HICANNOnWafer(Enum(1)), Wafer(33))
# disable all horizontal buses on h0
hicann = pyredman.Hicann()
for hbus in iter_all(HLineOnHICANN):
hicann.hbuses().disable(hbus)
self.marocco.defects.set(pyredman.Wafer())
self.marocco.defects.wafer().inject(h0, hicann)
pynn.setup(marocco=self.marocco)
n1 = 100
n2 = 100
p1 = pynn.Population(n1, pynn.EIF_cond_exp_isfa_ista)
p2 = pynn.Population(n2, pynn.EIF_cond_exp_isfa_ista)
self.marocco.manual_placement.on_hicann(p1, h0)
self.marocco.manual_placement.on_hicann(p2, h1)
n_post = 10
if mode == "Population":
src = p1
tgt = p2
exp_loss = len(src) * n_post
elif mode == "PopulationView":
src = p1[n1 // 2:n1]
tgt = p2[n2 // 2:n2]
exp_loss = len(src) * n_post
elif mode == "Assembly":
src = pynn.Assembly(p1, p2)
tgt = p2
exp_loss = len(p1) * n_post
conn = pynn.FixedNumberPostConnector(n_post,
allow_self_connections=True,
weights=1.)
proj = pynn.Projection(src, tgt, conn, target='excitatory')
pynn.run(100)
pynn.end()
# check stats
self.assertEqual(exp_loss,
self.marocco.stats.getSynapseLossAfterL1Routing())
self.assertEqual(exp_loss, self.marocco.stats.getSynapseLoss())
# check weight matrices
orig_weights = proj.getWeights(format="array")
mapped_weights = self.marocco.stats.getWeights(proj)
lost_syns = np.logical_and(np.isfinite(orig_weights),
np.isnan(mapped_weights))
self.assertEqual(exp_loss, np.count_nonzero(lost_syns))
def big_network(self):
pynn.setup(marocco=self.marocco)
synapses = 0
numberOfPopulations = random.randint(100, 150)
logging.debug("number of populations: %d" % (numberOfPopulations))
#print "numPops: %d" % (numberOfPopulations)
# FIXME: spuouriously fails, why?
#pops = [ Population(random.randint(50, 85), EIF_cond_exp_isfa_ista) for x in
#range(numberOfPopulations) ]
pops = [
pynn.Population(80, pynn.EIF_cond_exp_isfa_ista)
for x in range(numberOfPopulations)
]
for idx, pop in enumerate(pops):
connectorE = pynn.FixedProbabilityConnector(
p_connect=0.20, allow_self_connections=True, weights=1.)
connectorI = pynn.FixedProbabilityConnector(
p_connect=0.10, allow_self_connections=True, weights=1.)
# build ring like network topology
proj = pynn.Projection(pop,
pops[(idx + 1) % len(pops)],
connectorE,
target='excitatory')
synapses += np.count_nonzero(proj.getWeights())
proj = pynn.Projection(pop,
pops[(idx + 1) % len(pops)],
connectorI,
target='inhibitory')
synapses += np.count_nonzero(proj.getWeights())
# add poisson stimulus
source = pynn.Population(1, pynn.SpikeSourcePoisson, {'rate': 2})
proj = pynn.Projection(source,
pop,
connectorE,
target='excitatory')
synapses += np.count_nonzero(proj.getWeights())
pynn.run(100)
pynn.end()
logging.debug("synapses counted in python: %d", synapses)
return synapses
def test_issue1681(self):
con = pynn.FixedProbabilityConnector(p_connect=1.0, weights=0.004)
pynn.setup(marocco=self.marocco)
pop1 = pynn.Population(10, pynn.IF_cond_exp, {})
ipu1 = pynn.Population(1, pynn.SpikeSourceArray, {'spike_times': []})
pro1 = pynn.Projection(ipu1, pop1, con, target='excitatory')
# Issue 1681 "IndexError after mapping ends" is triggered by adding a
# population after a projection:
# Expected Output: NO ERROR
# Actual Output: "IndexError: vector::_M_range_check" (i.e. abnormal termination)
pop2 = pynn.Population(10, pynn.IF_cond_exp, {})
pynn.run(0)
def test_projection(self):
size_a = random.randint(1, 1000)
size_b = random.randint(1, 1000)
pop_a = pyhmf.Population(size_a, pyhmf.IF_cond_exp)
pop_b = pyhmf.Population(size_b, pyhmf.IF_cond_exp)
pro = pyhmf.Projection(pop_a, pop_b, pyhmf.AllToAllConnector())
# ECM: iteration over Connections?
#self.assertEqual(len(pro), len(list(pro.__iter__())))
#self.assertEqual(len(pro), len(list(pro.all())))
self.assertEqual(size_a * size_b, len(pro))
self.assertEqual(size_a * size_b, pro.size)
def test_external_sources_drivers(self, nsources):
"""
A lot external sources are placed
no error should be thrown
the sources should be split
"""
pylogging.set_loglevel(pylogging.get("marocco"),
pylogging.LogLevel.DEBUG)
pylogging.set_loglevel(pylogging.get("Calibtic"),
pylogging.LogLevel.ERROR)
pynn.setup(marocco=self.marocco)
self.marocco.neuron_placement.default_neuron_size(4)
# ensure a limited synapse driver chain length.
self.marocco.synapse_routing.driver_chain_length(3)
# if synapse loss occours we want to handle it on our own
self.marocco.continue_despite_synapse_loss = True
target = pynn.Population(1, pynn.IF_cond_exp, {})
hicann = C.HICANNOnWafer(Enum(100))
self.marocco.manual_placement.on_hicann(target, hicann)
exsource = pynn.Population(nsources, pynn.SpikeSourcePoisson,
{'rate': 1.})
proj = pynn.Projection(exsource, target,
pynn.AllToAllConnector(weights=1.))
# access to proj so flake8 keeps silent
proj.size
pynn.run(0)
pynn.end()
results = self.load_results()
synapses = results.synapse_routing.synapses()
placement = results.placement
# test for synapse loss
self.assertEqual(nsources, synapses.size())
for dnc in C.iter_all(C.DNCMergerOnWafer):
PonDNC = placement.find(dnc) # PopulationOnDNC
if PonDNC:
## with a neuron size of 4 and a chain length of 3,
## around 12 sources can fit into a merger
self.assertTrue(len(PonDNC) <= 12)
def test_popview_external_source(self):
pynn.setup(marocco=self.marocco)
neuron_size = 4
self.marocco.neuron_placement.default_neuron_size(neuron_size)
size = 10
pop_ext = pynn.Population(size, pynn.SpikeSourcePoisson, {'rate':2})
pop_ext_1 = pynn.Population(size, pynn.SpikeSourcePoisson, {'rate':2})
pop = pynn.Population(size, pynn.IF_cond_exp, {})
connector = pynn.AllToAllConnector(weights=1)
projections = [
pynn.Projection(pop_ext, pop, connector, target='excitatory'),
pynn.Projection(pop_ext_1, pop, connector, target='excitatory'),
]
hicann = C.HICANNOnWafer(Enum(121))
hicann_1 = C.HICANNOnWafer(Enum(122))
pop_view = pynn.PopulationView(pop_ext,list(range(1,size,2)))
pop_view_1 = pynn.PopulationView(pop_ext,list(range(0,size,2)))
pop_1_view = pynn.PopulationView(pop_ext_1,list(range(1,size//2)))
pop_1_view_1 = pynn.PopulationView(pop_ext_1,list(range(size-2,size//2,-1)))
pop_1_auto_placement = pynn.PopulationView(pop_ext_1,[0,size//2,size-1])
self.marocco.manual_placement.on_hicann(pop_view, hicann)
self.marocco.manual_placement.on_hicann(pop_view_1, hicann_1)
self.marocco.manual_placement.on_hicann(pop_1_view, hicann)
self.marocco.manual_placement.on_hicann(pop_1_view_1, hicann_1)
pynn.run(0)
pynn.end()
results = self.load_results()
for nrn in pop_view:
placement_item, = results.placement.find(nrn)
self.assertEqual(hicann, placement_item.dnc_merger().toHICANNOnWafer())
for nrn in pop_view_1:
placement_item, = results.placement.find(nrn)
self.assertEqual(hicann_1, placement_item.dnc_merger().toHICANNOnWafer())
for nrn in pop_1_view:
placement_item, = results.placement.find(nrn)
self.assertEqual(hicann, placement_item.dnc_merger().toHICANNOnWafer())
for nrn in pop_1_view_1:
placement_item, = results.placement.find(nrn)
self.assertEqual(hicann_1, placement_item.dnc_merger().toHICANNOnWafer())
for nrn in pop_1_auto_placement:
placement_item, = results.placement.find(nrn)
self.assertIsNotNone(placement_item.dnc_merger().toHICANNOnWafer())
def test(self):
wafer = 99999 # a wafer for which no redman data is availale
hicann = 82
neuron_number = 12
marocco = PyMarocco()
marocco.neuron_placement.default_neuron_size(4)
marocco.backend = PyMarocco.Without
marocco.default_wafer = C.Wafer(wafer)
used_hicann = C.HICANNGlobal(C.HICANNOnWafer(Enum(hicann)),
C.Wafer(wafer))
used_hicann # prevent pep8 warning of unused variable
pynn.setup(marocco=marocco)
pop = pynn.Population(1, pynn.IF_cond_exp)
topleft = C.NeuronOnWafer(C.NeuronOnHICANN(X(neuron_number), Y(0)),
C.HICANNOnWafer(Enum(hicann)))
logical_neuron = LogicalNeuron.rectangular(topleft, size=4)
marocco.manual_placement.on_neuron(pop, logical_neuron)
with self.assertRaises(RuntimeError):
pynn.run(0)
pynn.end()
def test_on_neurons(self, pop_size):
pynn.setup(marocco=self.marocco)
pop = pynn.Population(pop_size, pynn.IF_cond_exp, {})
neuron_block = C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(3))
logical_neurons = [
(LogicalNeuron.on(neuron_block)
.add(C.NeuronOnNeuronBlock(X(3), Y(0)), 2)
.add(C.NeuronOnNeuronBlock(X(3), Y(1)), 2)
.done()),
(LogicalNeuron.on(neuron_block)
.add(C.NeuronOnNeuronBlock(X(11), Y(0)), 2)
.add(C.NeuronOnNeuronBlock(X(11), Y(1)), 2)
.done()),
]
self.marocco.manual_placement.on_neuron(pop, logical_neurons)
if pop_size != len(logical_neurons):
with self.assertRaises(RuntimeError):
pynn.run(0)
pynn.end()
return
pynn.run(0)
pynn.end()
results = self.load_results()
for nrn, logical_neuron in zip(pop, logical_neurons):
placement_item, = results.placement.find(nrn)
self.assertEqual(logical_neuron, placement_item.logical_neuron())
def test_on_neuron_block(self, size):
pynn.setup(marocco=self.marocco)
neuron_size = 4
self.marocco.neuron_placement.default_neuron_size(neuron_size)
neuron_block = C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(3))
pop = pynn.Population(size, pynn.IF_cond_exp, {})
self.marocco.manual_placement.on_neuron_block(pop, neuron_block)
if neuron_size * size > C.NeuronOnNeuronBlock.enum_type.size:
with self.assertRaises(RuntimeError):
pynn.run(0)
pynn.end()
return
pynn.run(0)
pynn.end()
results = self.load_results()
for nrn in pop:
placement_item, = results.placement.find(nrn)
logical_neuron = placement_item.logical_neuron()
self.assertEqual(neuron_size, logical_neuron.size())
for denmem in logical_neuron:
self.assertEqual(neuron_block, denmem.toNeuronBlockOnWafer())
def test_popview_on_neuron(self):
pynn.setup(marocco=self.marocco)
pop = pynn.Population(4, pynn.IF_cond_exp, {})
neuron_block = C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(3))
neuron_block_1 = C.NeuronBlockOnWafer(C.NeuronBlockOnHICANN(2))
logical_neuron = (LogicalNeuron.on(neuron_block)
.add(C.NeuronOnNeuronBlock(X(3), Y(0)), 2)
.add(C.NeuronOnNeuronBlock(X(3), Y(1)), 2)
.done())
logical_neuron_1 = (LogicalNeuron.on(neuron_block_1)
.add(C.NeuronOnNeuronBlock(X(4), Y(0)), 2)
.add(C.NeuronOnNeuronBlock(X(4), Y(1)), 2)
.done())
popview = pynn.PopulationView(pop,[0])
popview_1 = pynn.PopulationView(pop,[2])
popview_auto_placement= pynn.PopulationView(pop,[1,3])
self.marocco.manual_placement.on_neuron(popview, logical_neuron)
self.marocco.manual_placement.on_neuron(popview_1, logical_neuron_1)
pynn.run(0)
pynn.end()
results = self.load_results()
placement_item, = results.placement.find(popview[0])
self.assertEqual(logical_neuron, placement_item.logical_neuron())
placement_item, = results.placement.find(popview_1[0])
self.assertEqual(logical_neuron_1, placement_item.logical_neuron())
for nrn in popview_auto_placement:
placement_item, = results.placement.find(nrn)
self.assertIsNotNone(placement_item.logical_neuron())
def test_Constructor(self):
import numpy
import pymarocco
marocco = pymarocco.PyMarocco()
marocco.calib_backend = pymarocco.PyMarocco.CalibBackend.Default
pynn.setup(marocco=marocco)
N = 10
model = pynn.IF_cond_exp
selector = numpy.array(
[random.choice([True, False]) for x in range(0, N)])
pop = pynn.Population(N, model)
pv = pynn.PopulationView(pop, selector)
self.assertEqual(len(pv), len(numpy.where(selector == True)[0]))
# now a selection with wrong size is given
wrong_selector = numpy.array(
[random.choice([True, False]) for x in range(0, 2 * N)])
with self.assertRaises(RuntimeError):
pv = pynn.PopulationView(pop, wrong_selector)
pynn.run(100)
