added masking to gauss err-cell

ngclearn/components/neurons/graded/gaussianErrorCell.py

@@ -62,15 +62,16 @@ class GaussianErrorCell(JaxComponent): ## Rate-coded/real-valued error unit/cell
 
         n_units: number of cellular entities (neural population size)
 
-        refract_time: relative refractory period time (ms; Default: 0 ms)
+        tau_m: (Unused -- currently cell is a fixed-point model)
+
+        leakRate: (Unused -- currently cell is a fixed-point model)
     """
-    def __init__(self, name, n_units, refract_time=0., batch_size=1, **kwargs):
+    def __init__(self, name, n_units, batch_size=1, **kwargs):
         super().__init__(name, **kwargs)
 
         ## Layer Size Setup
         self.n_units = n_units
         self.batch_size = batch_size
-        self.refract_T = refract_time  # ms ## refractory period
 
         ## Convolution shape setup
         self.width = self.height = n_units
@@ -83,47 +84,45 @@ def __init__(self, name, n_units, refract_time=0., batch_size=1, **kwargs):
         self.target = Compartment(restVals) # target. input wire
         self.dtarget = Compartment(restVals) # derivative target
         self.modulator = Compartment(restVals + 1.0) # to be set/consumed
-        self.rfr = Compartment(restVals + self.refract_T) ## refractory variable(s)
+        self.mask = Compartment(restVals + 1.0)
 
     @staticmethod
-    def _advance_state(dt, refract_T, mu, dmu, target, dtarget, modulator, rfr):
-        mask = (rfr >= refract_T) * 1.
+    def _advance_state(dt, mu, dmu, target, dtarget, modulator, mask):
         ## compute Gaussian error cell output
         dmu, dtarget, L = _run_cell(dt, target * mask, mu * mask)
         dmu = dmu * modulator * mask
         dtarget = dtarget * modulator * mask
-        if refract_T > 0.: ## if non-zero refractory times used, then...
-            rfr = (rfr + dt) * (1. - target) + target * dt  # set refract to dt
-        return dmu, dtarget, L, rfr
+        mask = mask * 0. + 1. ## "eat" the mask as it should only apply at time t
+        return dmu, dtarget, L, mask
 
     @resolver(_advance_state)
-    def advance_state(self, dmu, dtarget, L, rfr):
+    def advance_state(self, dmu, dtarget, L, mask):
         self.dmu.set(dmu)
         self.dtarget.set(dtarget)
         self.L.set(L)
-        self.rfr.set(rfr)
+        self.mask.set(mask)
 
     @staticmethod
-    def _reset(refract_T, batch_size, n_units):
+    def _reset(batch_size, n_units):
         restVals = jnp.zeros((batch_size, n_units))
         dmu = restVals
         dtarget = restVals
         target = restVals
         mu = restVals
         modulator = mu + 1.
         L = 0.
-        rfr = restVals + refract_T
-        return dmu, dtarget, target, mu, modulator, L, rfr
+        mask = jnp.ones((batch_size, n_units))
+        return dmu, dtarget, target, mu, modulator, L, mask
 
     @resolver(_reset)
-    def reset(self, dmu, dtarget, target, mu, modulator, L, rfr):
+    def reset(self, dmu, dtarget, target, mu, modulator, L, mask):
         self.dmu.set(dmu)
         self.dtarget.set(dtarget)
         self.target.set(target)
         self.mu.set(mu)
         self.modulator.set(modulator)
         self.L.set(L)
-        self.rfr.set(rfr)
+        self.mask.set(mask)
 
     @classmethod
     def help(cls): ## component help function