def test_regularisation_spikes():
x = torch.ones(5, 10)
s = LIFFeedForwardState(torch.ones(10), torch.ones(10))
z, s = lif_feed_forward_step(x, s)
zr, rs = regularize_step(z, s)
assert torch.equal(z, zr)
assert rs == 0
z, s = lif_feed_forward_step(x, s)
zr, rs = regularize_step(z, s)
assert rs == 50
def test_regularisation_voltage():
x = torch.ones(5, 10)
s = LIFFeedForwardState(torch.ones(10), torch.ones(10))
z, s = lif_feed_forward_step(x, s)
zr, rs = regularize_step(z, s, accumulator=voltage_accumulator)
assert torch.equal(z, zr)
assert torch.equal(s.v, rs)
def test_regularisation_voltage_state():
x = torch.ones(5, 10)
state = torch.zeros(10)
s = LIFFeedForwardState(torch.ones(10), torch.ones(10))
z, s = lif_feed_forward_step(x, s)
# pytype: disable=wrong-arg-types
zr, rs = regularize_step(z,
s,
accumulator=voltage_accumulator,
state=state)
# pytype: enable=wrong-arg-types
assert torch.equal(z, zr)
assert torch.equal(s.v, rs)
def forward(self, z, s):
_, state = regularize_step(z, s, self.accumulator, self.state)
self.state = state
return z, self.state