Fix C code of Reshape when input is not c-contiguous

theano/tensor/basic.py

@@ -5300,7 +5300,7 @@ class Reshape(Op):
         return [tuple(oshape)]
 
     def c_code_cache_version(self):
-        return (1,)
+        return (2,)
 
     def c_code(self, node, name, inputs, outputs, sub):
         if isinstance(node.inputs[0], TensorVariable):
@@ -5324,11 +5324,18 @@ class Reshape(Op):
                         %(shp)s->data + ii * %(shp)s->strides[0]))[0];
             }
             Py_XDECREF(%(z)s);
-            %(z)s = (PyArrayObject *) PyArray_Newshape(%(x)s, &newshape, NPY_ANYORDER);
+            %(z)s = (PyArrayObject *) PyArray_Newshape(%(x)s, &newshape, PyArray_CORDER);
+            if (!%(z)s)
+            {
+                PyErr_Format(PyExc_ValueError,
+                             "Could not reshape array.");
+                %(fail)s;
+            }
             """ % locals()
         else:
             return Op.c_code(self, node, name, inputs, outputs, sub)
 
+
 def reshape(x, newshape, ndim=None, name=None):
     if ndim is None:
         ndim = get_vector_length(newshape)

theano/tensor/tests/test_basic.py

@@ -4284,7 +4284,16 @@ class T_reshape(unittest.TestCase):
         #basic to 1 dim(without list)
         c = reshape(b, as_tensor_variable(6), ndim=1)
         f = inplace_func([b], c)
-        assert numpy.all(f(numpy.asarray([[0,1,2],[3,4,5]])) == numpy.asarray([0,1,2,3,4,5]))
+
+        b_val1 = numpy.asarray([[0,1,2],[3,4,5]])
+        c_val1 = numpy.asarray([0,1,2,3,4,5])
+        b_val2 = b_val1.T
+        c_val2 = numpy.asarray([0,3,1,4,2,5])
+
+        f_out1 = f(b_val1)
+        f_out2 = f(b_val2)
+        assert numpy.all(f_out1 == c_val1), (f_out1, c_val1)
+        assert numpy.all(f_out2 == c_val2), (f_out2, c_val2)
         #print f.maker.fgraph.toposort()
         #check that we remove the useless reshape