--- a/pylearn/gd/sgd.py	Wed May 18 10:52:22 2011 -0400
+++ b/pylearn/gd/sgd.py	Wed May 18 10:52:42 2011 -0400
@@ -16,7 +16,7 @@
     """
     try:
         iter(stepsizes)
-    except:
+    except Exception:
         stepsizes = [stepsizes for p in params]
     if len(params) != len(grads):
         raise ValueError('params and grads have different lens')
@@ -27,11 +27,11 @@
     # if stepsizes is just a scalar, expand it to match params
     try:
         iter(stepsizes)
-    except:
+    except Exception:
         stepsizes = [stepsizes for p in params]
     try:
         iter(momentum)
-    except:
+    except Exception:
         momentum = [momentum for p in params]
     if len(params) != len(grads):
         raise ValueError('params and grads have different lens')
@@ -79,7 +79,8 @@
             raise TypeError('stepsize must be a scalar', stepsize)
 
         self.params = params
-        self.gparams = theano.tensor.grad(cost, self.params) if gradients is None else gradients
+        self.gparams = [theano.tensor.grad(cost, self.params)] if gradients is None else gradients
+        assert len(self.params) == len(self.gparams)
 
         self._updates = (dict((p, p - self.stepsize * g) for p, g in zip(self.params, self.gparams)))
         if updates is not None: