Fix c code subtensor when the input have 0 dims and the outputs 0 dims.

theano/tensor/basic.py

@@ -3307,8 +3307,25 @@ class Subtensor(Op):
         {
             %(fail)s;
         }
-        assert (xview->dimensions != %(x)s->dimensions);
-        assert (xview->strides != %(x)s->strides);
+
+        if ((xview->dimensions == %(x)s->dimensions)
+            && (%(x)s->dimensions != NULL))
+        {
+            PyErr_Format(PyExc_ValueError, "x and xview"
+                         "(with %%d dims) have the same dimensions"
+                         " pointors: %%p and %%p",
+                         %(x)s->nd, xview->dimensions, %(x)s->dimensions);
+            %(fail)s;
+        }
+        if (xview->strides == %(x)s->strides
+            && (%(x)s->dimensions != NULL))
+        {
+            PyErr_Format(PyExc_ValueError, "x and xview"
+                         "(with %%d dims) have the same strides"
+                         " pointors: %%p and %%p",
+                         %(x)s->nd, xview->strides, %(x)s->strides);
+            %(fail)s;
+        }
 
         for (; outer_ii < %(len_is_slice)s; ++outer_ii)
         {
@@ -3425,7 +3442,7 @@ class Subtensor(Op):
 
     @staticmethod
     def helper_c_code_cache_version():
-        return (2,)
+        return (3,)
 
     def c_code(self, node, name, inputs, outputs, sub): #DEBUG
         part0 = self.helper_c_code(node, name, inputs, outputs, sub,
@@ -3446,6 +3463,8 @@ class Subtensor(Op):
 
     def c_code_cache_version(self):
         hv = self.helper_c_code_cache_version()
+        if len(hv) == 0:
+            return ()
         return (1, hv)
 
     def R_op(self, inputs, eval_points):

theano/tensor/tests/test_basic.py

@@ -1957,6 +1957,22 @@ class T_subtensor(unittest.TestCase):
             self.assertTrue(tval.shape == (2,))
             self.assertTrue(numpy.allclose(tval, n.get_value()[idx]))
 
+    def test1_0_dims(self):
+        n = self.shared(numpy.ones((), dtype=self.dtype))
+        t = theano.tensor.Subtensor([])(n)
+        self.assertTrue(isinstance(t.owner.op, Subtensor))
+        # Silence expected error messages
+        _logger = logging.getLogger('theano.gof.opt')
+        oldlevel = _logger.level
+        _logger.setLevel(logging.CRITICAL)
+        mode = self.mode
+        self.mode = mode.excluding("local_useless_subtensor")
+        try:
+            self.eval_output_and_check(t)
+        finally:
+            self.mode = mode
+            _logger.setLevel(oldlevel)
+
     def test1_err_invalid(self):
         n = self.shared(numpy.ones(1, dtype=self.dtype))
         try: