merge

theano/tensor/nnet/nnet.py

@@ -116,7 +116,7 @@ class SoftmaxWithBias(gof.Op):
         if ((%(x)s->dimensions[1] != %(b)s->dimensions[0]))
         {
             PyErr_Format(PyExc_ValueError, "number of columns in x (%%ld) does not match length of b (%%ld)",
-            %(x)s->dimensions[1], %(b)s->dimensions[0]);
+                (long int)%(x)s->dimensions[1], (long int)%(b)s->dimensions[0]);
             %(fail)s;
         }
 
@@ -554,7 +554,7 @@ class CrossentropySoftmaxArgmax1HotWithBias(gof.Op):
         if (%(x)s->dimensions[0] != %(y_idx)s->dimensions[0])
         {
             PyErr_Format(PyExc_ValueError, "number of rows in x (%%ld) does not match length of y (%%ld)",
-            %(x)s->dimensions[0], %(y_idx)s->dimensions[0]);
+                (long int)%(x)s->dimensions[0], (long int)%(y_idx)s->dimensions[0]);
             %(fail)s;
         }
 

theano/tensor/opt.py

@@ -379,10 +379,13 @@ class ShapeFeature(object):
             #
             # worst case, we loop over shape_of and replace things
             raise NotImplementedError(s_i)
-        elif s_i.type == T.lscalar:
+        elif s_i.type.dtype[:3] in ('int', 'uint'):
+            if getattr(s_i.type, 'ndim', 0):
+                raise TypeError('Shape element must be scalar', s_i)
             return s_i
         else:
-            raise TypeError('Unsupported shape element', s_i, s_i.type)
+            raise TypeError('Unsupported shape element', 
+                    s_i, type(s_i), getattr(s_i, 'type', None))
 
     def set_shape(self, r, s):
         assert r not in self.shape_of
@@ -504,6 +507,7 @@ def local_shape_i_lift(node):
     if inode and isinstance(inode.op, Elemwise) and inode.op.scalar_op.nin==1:
         return node.env.shape_feature.shape_of[input]
 
+
 register_canonicalize(local_shape_i_lift)
 register_specialize(local_shape_i_lift)