Raises an Exception when trying to compute the gradient of a non-scalar cost.

theano/tensor/basic.py

@@ -3978,9 +3978,9 @@ outer = Outer()
 
 def grad(cost, wrt, g_cost=None, consider_constant=[], warn_type=False):
     """
-    :type cost: `Variable`
+    :type cost: Scalar (0-dimensional) `Variable`
     :type wrt: `Variable` or list of `Variable`s.
-    :type g_cost: `Variable` broadcastable to size of `cost`, or None
+    :type g_cost: Scalar `Variable`, or None
     :param g_cost: an expression for the gradient through cost.  The default is
         ``ones_like(cost)``.
     :param consider_constant: a list of expressions not to backpropagate through
@@ -4003,9 +4003,11 @@ def grad(cost, wrt, g_cost=None, consider_constant=[], warn_type=False):
         raise TypeError('In tensor.grad(), cost argument should be a TensorVariable.', cost)
 
     if cost.type.ndim:
-        _warn('the passing of a non-scalar cost to theano.tensor.grad() is deprecated.'
-                '  Use the lower-level '
-                'theano.gradient if you really want to do this')
+        raise TypeError(
+                'In tensor.grad, "cost" argument should be a scalar, but ndim'
+                ' is %i (should be 0). If you want to compute the gradient of'
+                ' the sum of cost, you should use cost.sum().'
+                % cost.type.ndim)
 
     if g_cost is None:
         g_cost = ones_like(cost)