compatible dimes are now fixed

theano/tensor/opt.py

@@ -4162,18 +4162,22 @@ def local_sum_prod_div_dimshuffle(node):
                     isinstance(numerator.owner.op, T.DimShuffle)):
                 # Check compatibility
                 new_order = numerator.owner.op.new_order
+                compatible_dims = True
                 for ax in axis:
-                    if ax < len(new_order) and new_order[ax] == 'x':
-                        _logger.warn('WARNING: Your current code is fine, but'
-                                     ' Theano versions between '
-                                     'rev. 3bd9b789f5e8 (2010-06-16) and'
-                                     ' cfc6322e5ad4 (2010-08-03) would '
-                                     'have given an incorrect result. '
-                                     'To disable this warning, set the Theano'
-                                     ' flag warn.sum_div_dimshuffle_bug to'
-                                     ' False.')
+                    if len(new_order) <= ax or new_order[ax] != 'x':
+                        compatible_dims = False
                         break
 
+                if compatible_dims:
+                    _logger.warn('WARNING: Your current code is fine, but'
+                                 ' Theano versions between '
+                                 'rev. 3bd9b789f5e8 (2010-06-16) and'
+                                 ' cfc6322e5ad4 (2010-08-03) would '
+                                 'have given an incorrect result. '
+                                 'To disable this warning, set the Theano'
+                                 ' flag warn.sum_div_dimshuffle_bug to'
+                                 ' False.')
+
             if denominator.owner and isinstance(denominator.owner.op,
                                                 T.DimShuffle):
                 dimshuffle_input = denominator.owner.inputs[0]
@@ -4237,10 +4241,11 @@ def local_sum_prod_div_dimshuffle(node):
                     elif isinstance(node.op, T.elemwise.Prod):
                         op_on_compatible_dims = T.prod(
                             numerator, axis=compatible_dims)
+                        dtype = numerator.dtype
                         div_op = T.true_div(
                             op_on_compatible_dims,
                             (optimized_dimshuffle **
-                                T.prod([numerator.shape[ax]
+                                T.prod([numerator.shape[ax].astype(dtype)
                                         for ax in compatible_dims])))
                         op_on_incompatible_dims = T.prod(
                             div_op,