Additions for inhibition stuff

ngclearn/components/base_monitor.py

@@ -124,9 +124,10 @@ def watch(self, compartment, window_length):
         """
         cs, end = self._add_path(compartment.path)
 
+        dtype = compartment.value.dtype
         shape = compartment.value.shape
-        new_comp = Compartment(np.zeros(shape))
-        new_comp_store = Compartment(np.zeros((window_length, *shape)))
+        new_comp = Compartment(np.zeros(shape, dtype=dtype))
+        new_comp_store = Compartment(np.zeros((window_length, *shape), dtype=dtype))
 
         comp_key = "*".join(compartment.path.split("/"))
         store_comp_key = comp_key + "*store"

ngclearn/components/input_encoders/poissonCell.py

@@ -46,7 +46,7 @@ class PoissonCell(JaxComponent):
     """
 
     @deprecate_args(max_freq="target_freq")
-    def __init__(self, name, n_units, target_freq=0., batch_size=1, **kwargs):
+    def __init__(self, name, n_units, target_freq=63.75, batch_size=1, **kwargs):
         super().__init__(name, **kwargs)
 
         ## Constrained Bernoulli meta-parameters

ngclearn/components/other/varTrace.py

@@ -5,7 +5,7 @@
 from ngclearn.utils import tensorstats
 
 @partial(jit, static_argnums=[4])
-def _run_varfilter(dt, x, x_tr, decayFactor, a_delta=0.):
+def _run_varfilter(dt, x, x_tr, decayFactor, gamma_tr, a_delta=0.):
     """
     Run variable trace filter (low-pass filter) dynamics one step forward.
 
@@ -22,7 +22,7 @@ def _run_varfilter(dt, x, x_tr, decayFactor, a_delta=0.):
     Returns:
         updated trace/filter value/state
     """
-    _x_tr = x_tr * decayFactor
+    _x_tr = gamma_tr * x_tr * decayFactor
     #x_tr + (-x_tr) * (dt / tau_tr) = (1 - dt/tau_tr) * x_tr
     if a_delta > 0.: ## perform additive form of trace ODE
         _x_tr = _x_tr + x * a_delta
@@ -64,13 +64,14 @@ class VarTrace(JaxComponent): ## low-pass filter
     """
 
     # Define Functions
-    def __init__(self, name, n_units, tau_tr, a_delta, decay_type="exp",
+    def __init__(self, name, n_units, tau_tr, a_delta, gamma_tr=1, decay_type="exp",
                  batch_size=1, **kwargs):
         super().__init__(name, **kwargs)
 
         ## Trace control coefficients
         self.tau_tr = tau_tr ## trace time constant
         self.a_delta = a_delta ## trace increment (if spike occurred)
+        self.gamma_tr = gamma_tr
         self.decay_type = decay_type ## lin --> linear decay; exp --> exponential decay
 
         ## Layer Size Setup
@@ -83,17 +84,20 @@ def __init__(self, name, n_units, tau_tr, a_delta, decay_type="exp",
         self.trace = Compartment(restVals)
 
     @staticmethod
-    def _advance_state(dt, decay_type, tau_tr, a_delta, inputs, trace):
-        ## compute the decay factor
-        decayFactor = 0. ## <-- pulse filter decay (default)
+    def _advance_state(dt, decay_type, tau_tr, a_delta, gamma_tr, inputs, trace):
+        decayFactor = 0.
         if "exp" in decay_type:
             decayFactor = jnp.exp(-dt/tau_tr)
         elif "lin" in decay_type:
             decayFactor = (1. - dt/tau_tr)
-        ## else "step" == decay_type, yielding a step/pulse-like filter
-        trace = _run_varfilter(dt, inputs, trace, decayFactor, a_delta)
-        outputs = trace
-        return outputs, trace
+
+        _x_tr = gamma_tr * trace * decayFactor
+        if a_delta > 0.:
+            _x_tr = _x_tr + inputs * a_delta
+        else:
+            _x_tr = _x_tr * (1. - inputs) + inputs
+
+        return trace, trace
 
     @resolver(_advance_state)
     def advance_state(self, outputs, trace):

ngclearn/components/synapses/denseSynapse.py

@@ -47,8 +47,8 @@ def __init__(self, name, shape, weight_init=None, bias_init=None,
         self.bias_init = bias_init
 
         ## Synapse meta-parameters
-        self.shape = shape ## shape of synaptic efficacy matrix
-        self.Rscale = resist_scale ## post-transformation scale factor
+        self.shape = shape
+        self.Rscale = resist_scale
 
         ## Set up synaptic weight values
         tmp_key, *subkeys = random.split(self.key.value, 4)

ngclearn/utils/viz/synapse_plot.py

@@ -138,13 +138,13 @@ def visualize_gif(frames, path='.', name='tmp', suffix='.jpg', **kwargs):
     _frames = [f.astype(jnp.uint8) for f in frames]
     iio.imwrite(path + '/' + name + '.gif', _frames, **kwargs)
 
-def make_video(f_start, f_end, path, prefix, suffix='.jpg', skip=1):
+def make_video(f_start, f_end, path, prefix, suffix='.jpg', skip=1, **kwargs):
     images = []
     for i in range(f_start, f_end+1, skip):
         print("Reading frame " + str(i))
         images.append(iio.imread(path + "/" + prefix + str(i) + suffix))
     print("writing gif")
-    iio.imwrite(path + '/training.gif', images, loop=0, duration=200)
+    iio.imwrite(path + '/training.gif', images, **kwargs)
 
 
 # def visualize_norm(thetas, sizes, prefix, suffix='.jpg'):