--- a/pylearn/algorithms/sandbox/DAA_inputs_groups.py	Thu May 21 12:18:36 2009 -0400
+++ b/pylearn/algorithms/sandbox/DAA_inputs_groups.py	Thu May 21 12:54:41 2009 -0400
@@ -175,10 +175,10 @@
 				self.Maskdown = [self.Maskdown]
 		listweights = []
 		listweightsenc = []
-		if self.input is None:
+		if not(self.auxinput is None):
 			listweights += [w*m for w,m in zip(self.Maskup,self.wauxenc)] + [w*m for w,m in zip(self.Maskdown,self.wauxdec)]
 			listweightsenc += [w*m for w,m in zip(self.Maskup,self.wauxenc)]
-		if self.auxinput is None:
+		if not(self.input is None):
 			listweights += [self.wenc,self.wdec]
 			listweightsenc += [self.wenc]
 		self.regularization = self.reg_coef * get_reg_cost(listweights,'l2')
@@ -198,16 +198,18 @@
 		if not hasattr(self,'params'):
 			self.params = []
 		self.params += [self.benc]
+		self.paramsenc = self.params
 		if not(self.input is None):
 			self.params += [self.wenc] + [self.bdec]
+			self.paramsenc += [self.wenc]
 		if not(self.auxinput is None):
 			self.params += self.wauxenc + self.bauxdec
-		self.paramsenc = self.params
+			self.paramsenc += self.wauxenc
 		if not(self.tie_weights):
 			if not(self.input is None):
-				self.params += [self.bdec]
+				self.params += [self.wdec]
 			if not(self.auxinput is None):
-				self.params += self.wauxdec + self.bauxdec
+				self.params += self.wauxdec
 	
 	# DEPENDENCY: define_cost, define_gradients
 	def define_gradients(self):