minor edits and doc edit

Author: ago109

ngclearn/engine/cables/dcable.py

@@ -130,7 +130,7 @@ def __init__(self, inp, out, init_kernels=None, shared_param_path=None,
         if self.shared_param_path is not None:
             cable_to_mirror, path_type = shared_param_path
             """
-                path_type = A, A^T, -A^T, A^T+b, -A^T+b
+                path_type = A, A^T, A+b, -A^T, A^T+b, -A^T+b
             """
             self.path_type = path_type
             A = cable_to_mirror.params["A"]

ngclearn/engine/nodes/node.py

@@ -75,15 +75,21 @@ def compile(self):
                 comp_dim = curr_comp.shape[1]
                 comp_var_name = curr_comp.name
                 comp_var_name = comp_var_name[0:curr_comp.name.index(":"):1]
-                self.compartments[cname] = \
-                    tf.Variable(tf.zeros([self.batch_size,comp_dim]), name=comp_var_name)
+                if self.do_inplace == True:
+                    self.compartments[cname] = \
+                        tf.Variable(tf.zeros([self.batch_size,comp_dim]), name=comp_var_name)
+                else:
+                    self.compartments[cname] = tf.zeros([self.batch_size,comp_dim])
         for mname in self.mask_names:
             curr_mask = self.masks.get(mname)
             if curr_mask is not None:
                 mask_var_name = curr_mask.name
                 mask_var_name = mask_var_name[0:curr_mask.name.index(":"):1]
                 mask_dim = curr_mask.shape[1]
-                self.masks[mname] = tf.Variable(tf.ones([self.batch_size,mask_dim]), name=mask_var_name)
+                if self.do_inplace == True:
+                    self.masks[mname] = tf.Variable(tf.ones([self.batch_size,mask_dim]), name=mask_var_name)
+                else:
+                    self.masks[mname] = tf.ones([self.batch_size,mask_dim])
         info["object_type"] = self.node_type
         info["object_name"] = self.name
         info["n_connected_cables"] = len(self.connected_cables)

ngclearn/generator/temporal/noisy_sin.py

@@ -40,11 +40,13 @@ def sample(self):
         """
         # increment the internal tracking of x
         x = self.x_prev + self.dt
+        x = x.astype(np.float32)
         # compute the Gaussian/white-noise corrupted sine wave output
         y = np.sin(x) + np.random.normal(size=self.sigma.shape) * self.sigma
+        y = y.astype(np.float32)
         # Store x sample into x_prev state
         self.x_prev = x # this step ensures that the next noise sample is dependent upon current one
-        return x
+        return y
 
     def reset(self):
         """
@@ -53,4 +55,6 @@ def reset(self):
         if self.x_initial is not None:
             self.x_prev = self.x_initial
         else: # reset the noise process back to zero
-            self.x_prev = np.zeros_like(self.mean)
+            self.x_prev = np.zeros_like(self.sigma)
+        self.x_prev = self.x_prev.astype(np.float32)
+        

ngclearn/generator/temporal/oh_process.py

@@ -48,6 +48,7 @@ def sample(self):
             + self.theta * (self.mean - self.x_prev) * self.dt
             + self.std_dev * np.sqrt(self.dt) * np.random.normal(size=self.mean.shape)
         )
+        x = x.astype(np.float32)
         # Store x sample into x_prev state
         self.x_prev = x # this step ensures that the next noise sample is dependent upon current one
         return x
@@ -60,3 +61,4 @@ def reset(self):
             self.x_prev = self.x_initial
         else: # reset the noise process back to zero
             self.x_prev = np.zeros_like(self.mean)
+        self.x_prev = self.x_prev.astype(np.float32)