made some corrections to bern err-cell and heb syn

Author: Alexander Ororbia

ngclearn/components/neurons/graded/bernoulliErrorCell.py

@@ -102,14 +102,14 @@ def _reset(batch_size, shape): ## reset core components/statistics
         _shape = (batch_size, shape[0])
         if len(shape) > 1:
             _shape = (batch_size, shape[0], shape[1], shape[2])
-        restVals = jnp.zeros(_shape)
+        restVals = jnp.zeros(_shape) ## "rest"/reset values
         dp = restVals
         dtarget = restVals
         target = restVals
         p = restVals
-        modulator = mu + 1.
-        L = 0. #jnp.zeros((1, 1))
-        mask = jnp.ones(_shape)
+        modulator = restVals + 1. ## reset modulator signal
+        L = 0. #jnp.zeros((1, 1)) ## rest loss
+        mask = jnp.ones(_shape) ## reset mask
         return dp, dtarget, target, p, modulator, L, mask
 
     @resolver(_reset)

ngclearn/components/synapses/hebbian/hebbianSynapse.py

@@ -48,13 +48,13 @@ def _calc_update(pre, post, W, w_bound, is_nonnegative=True, signVal=1.,
         dW = dW * (w_bound - jnp.abs(W))
 
     if prior_type == "l2" or prior_type == "ridge":
-        dW_reg = W
+        dW_reg = -W
     if prior_type == "l1" or prior_type == "lasso":
-        dW_reg = jnp.sign(W)
+        dW_reg = -jnp.sign(W)
     if prior_type == "l1l2" or prior_type == "elastic_net":
         l1_ratio = prior_lmbda[1]
         prior_lmbda = prior_lmbda[0]
-        dW_reg = jnp.sign(W) * l1_ratio + W * (1-l1_ratio)/2
+        dW_reg = -jnp.sign(W) * l1_ratio - W * (1-l1_ratio)/2
 
     dW = dW + prior_lmbda * dW_reg
     return dW * signVal, db * signVal