Merge branch 'v3' of github.com:NACLab/ngc-learn into v3

Author: rxng8

ngclearn/components/base_monitor.py

@@ -1,8 +1,8 @@
 import json
 
-from ngclearn import Component, Compartment, transition
+from ngclearn import Component, Compartment #, transition
 from ngclearn import numpy as np
-from ngcsimlib.utils import get_current_path
+#from ngcsimlib.utils import get_current_path
 from ngcsimlib.logger import warn, critical
 
 import matplotlib.pyplot as plt
@@ -68,7 +68,7 @@ def _record_internal(compartments):
             "monitor found in ngclearn.components or "
             "ngclearn.components.lava (If using lava)")
 
-    @transition(None, True)
+    #@transition(None, True)
     @staticmethod
     def reset(component):
         """
@@ -95,7 +95,7 @@ def _reset(**kwargs):
         # pure func, output compartments, args, params, input compartments
         return _reset, output_compartments, [], [], output_compartments
 
-    @transition(None, True)
+    #@transition(None, True)
     @staticmethod
     def record(component):
         output_compartments = []
@@ -265,8 +265,9 @@ def load(self, directory, **kwargs):
 
             for comp_path, shape in vals["stores"].items():
                 compartment_path = comp_path.split("/")[-1]
-                new_path = get_current_path() + "/" + "/".join(
-                    compartment_path.split("*")[-3:-1])
+                new_path = ""
+                # new_path = get_current_path() + "/" + "/".join(
+                #     compartment_path.split("*")[-3:-1])
 
                 cs, end = self._add_path(new_path)
 

ngclearn/components/monitor.py

@@ -1,5 +1,5 @@
 from ngclearn.components.base_monitor import Base_Monitor
-from ngclearn import transition
+#from ngclearn import transition
 
 class Monitor(Base_Monitor):
     """

tests/components/input_encoders/test_bernoulliCell.py

@@ -47,4 +47,4 @@ def clamp(x):
     assert_array_equal(outs, x_seq)
     #print(outs)
 
-test_bernoulliCell1()
+#test_bernoulliCell1()

tests/components/input_encoders/test_latencyCell.py

@@ -60,4 +60,4 @@ def clamp(x):
     ## output should equal input
     assert_array_equal(outs, targets)
 
-test_latencyCell1()
+#test_latencyCell1()

tests/components/input_encoders/test_phasorCell.py

@@ -44,4 +44,4 @@ def clamp(x):
     ## output should equal input
     assert_array_equal(outs, x_seq)
 
-test_phasorCell1()
+#test_phasorCell1()

tests/components/input_encoders/test_poissonCell.py

@@ -43,4 +43,4 @@ def clamp(x):
     ## output should equal input
     assert_array_equal(outs, x_seq)
 
-test_poissonCell1()
+#test_poissonCell1()

tests/components/neurons/graded/test_rewardErrorCell.py

@@ -58,13 +58,13 @@ def clamp_reward(x):
       reward_t = jnp.array([[reward_seq[0, ts]]])  ## get reward at time t
       clamp_reward(reward_t)
       advance_process.run(t=ts * 1., dt=dt)
-      mu_outs.append(a.mu.value)
-      rpe_outs.append(a.rpe.value)
-      accum_reward_outs.append(a.accum_reward.value)
+      mu_outs.append(a.mu.get())
+      rpe_outs.append(a.rpe.get())
+      accum_reward_outs.append(a.accum_reward.get())
 
   # Test evolve function
   evolve_process.run(t=10 * 1., dt=dt)
-  final_mu = a.mu.value
+  final_mu = a.mu.get()
   # print(f"final_mu: {final_mu}")
 
   mu_outs = jnp.concatenate(mu_outs, axis=1)
@@ -85,4 +85,4 @@ def clamp_reward(x):
   expected_final_mu = (1 - 1/10) * mu_outs[0, -1] + (1/10) * (accum_reward_outs[0, -1] / 10)
   np.testing.assert_allclose(final_mu, expected_final_mu, atol=1e-5)
 
-# test_rewardErrorCell()
+#test_rewardErrorCell()