Fixed Monitor issue; added last bit of ETH STDP definition; moved notebooks.

bindsnet/network/__init__.py

@@ -98,12 +98,6 @@ def run(self, inpts, time):
 			for monitor in self.monitors:
 				self.monitors[monitor].record()
 
-		# if self.train:
-		# 	# Normalize synapse weights.
-		# 	for synapse in self.connections:
-		# 		if type(self.connections[synapse]) == connections.STDPconnections:
-		# 			self.connections[synapse].normalize()
-
 		return spikes
 
 	def reset(self):
@@ -133,7 +127,8 @@ def get(self, var):
 
 	def record(self):
 		for var in self.state_vars:
-			self.recording[var] = torch.cat([self.recording[var], self.obj.__dict__[var]])
+			data = self.obj.__dict__[var].view(-1, 1)
+			self.recording[var] = torch.cat([self.recording[var], data], 1)
 
 	def reset(self):
 		self.recording = {var : torch.Tensor() for var in self.state_vars}

bindsnet/network/connections.py

@@ -1,16 +1,17 @@
 import torch
 
 
-def ETH_STDP(conn, nu_pre=1e-4, nu_post=1e-2):
+def ETH_STDP(conn, nu_pre=1e-4, nu_post=1e-2, norm=78.0):
 	# Post-synaptic.
 	conn.w += nu_post * (conn.source.x.view(conn.source.n,
 			1) * conn.target.s.float().view(1, conn.target.n))
 	# Pre-synaptic.
 	conn.w -= nu_pre * (conn.source.s.float().view(conn.source.n,
 							1) * conn.target.x.view(1, conn.target.n))
 
-	# Ensure that weights are within [0, self.wmax].
+	# Bound and re-normalize weights.
 	conn.w = torch.clamp(conn.w, 0, conn.wmax)
+	conn.w *= norm / conn.w.sum(0).view(1, -1)
 
 
 class Connection:

bindsnet/network/nodes.py

@@ -93,6 +93,7 @@ def __init__(self, n, traces=False, threshold=1.0, trace_tc=5e-2):
 		self.n = n  # No. of neurons.
 		self.traces = traces  # Whether to record synpatic traces.
 		self.threshold = threshold  # Spike threshold voltage.
+		self.v = torch.zeros_like(torch.Tensor(n))  # Neuron voltages.
 		self.s = torch.zeros_like(torch.Tensor(n))  # Spike occurences.
 
 		if self.traces:
@@ -108,7 +109,8 @@ def step(self, inpts, dt):
 				of inputs to the layer, with size equal to self.n.
 			dt (float): Simulation time step.
 		'''
-		self.s = inpts >= self.threshold  # Check for spiking neurons.
+		self.v = inpts
+		self.s = self.v >= self.threshold  # Check for spiking neurons.
 
 		if self.traces:
 			# Decay and set spike traces.