make theano raise an error if ndarray are not aligned and make a test for it.

theano/tensor/basic.py

@@ -606,6 +606,10 @@ class TensorType(Type):
             PyErr_SetString(PyExc_ValueError, "expected an ndarray");
             %(fail)s
         }
+        if (!PyArray_ISALIGNED(py_%(name)s)) {
+            PyErr_SetString(PyExc_ValueError, "expected an aligned array");
+            %(fail)s
+        }
         type_num_%(name)s = ((PyArrayObject*)py_%(name)s)->descr->type_num; //we expect %(type_num)s
         if (type_num_%(name)s != %(type_num)s) {
             PyErr_SetString(PyExc_ValueError, "expected %(type_num)s");
@@ -654,7 +658,7 @@ class TensorType(Type):
     def c_code_cache_version(self):
         scalar_version = scal.Scalar(self.dtype).c_code_cache_version()
         if scalar_version:
-            return (2,) + scalar_version
+            return (3,) + scalar_version
         else:
             return ()
 

theano/tensor/tests/test_basic.py

@@ -2688,6 +2688,25 @@ def test_mod_compile():
 
     f = theano.function([x,y],out)
 
+def test_unalign():
+    a = numpy.empty(1e6, dtype="b1,f8")['f1']
+    b = numpy.empty(1e6, dtype="b1,f8")['f1']
+    assert not a.flags.aligned
+    assert not b.flags.aligned
+    a[:] = numpy.random.rand(len(a))
+    b[:] = numpy.random.rand(len(b))
+    out_numpy = 2*a + 3*b
+
+    av,bv = tensor.vectors('ab')
+    f = theano.function([av,bv],2*av+3*bv)
+    f.maker.env.toposort()
+    try:
+        out_theano = f(a,b)
+    except ValueError:
+        pass
+    else:
+        raise Exception("Expected an error from Theano!")
+
 if __name__ == '__main__':
     if 1:
         unittest.main()