Add test to make sure that we shift things correctly for a single matrix with removed dimensions.

theano/tensor/tests/test_subtensor.py

@@ -20,8 +20,8 @@ from theano.compile import DeepCopyOp
 from theano.tensor import (MakeSlice, NotScalarConstantError, _shared,
                            as_tensor_variable, cscalar, ctensor3, dmatrix,
                            dscalar, dtensor4, dvector, fmatrix, fscalar,
-                           fvector, iscalar, lmatrix, lrow, lvector, matrix,
-                           vector)
+                           fvector, ftensor4, iscalar, lmatrix, lrow, lvector,
+                           matrix, vector)
 from theano.tensor.basic import DimShuffle
 from theano.tensor.subtensor import (AdvancedIncSubtensor,
                                      AdvancedIncSubtensor1, AdvancedSubtensor,
@@ -1349,6 +1349,7 @@ class TestAdvancedSubtensor(unittest.TestCase):
         self.v = fvector()
         self.m = dmatrix()
         self.t = ctensor3()
+        self.ft4 = ftensor4()
 
         self.ix1 = lvector()  # advanced 1d query
         self.ix12 = lvector()
@@ -1419,11 +1420,21 @@ class TestAdvancedSubtensor(unittest.TestCase):
         a = inc_subtensor(subt, subt)
 
         assert a.type == self.v.type, (a.type, self.v.type)
-        f = theano.function([self.v, self.ix2], a, allow_input_downcast=True)
+        f = theano.function([self.v, self.ix2], a, allow_input_downcast=True,
+                            mode=self.mode)
         aval = f([.4, .9, .1], [[1, 2],
                                 [1, 2]])
         assert numpy.allclose(aval, [.4, .9 * 3, .1 * 3])
 
+    def test_adv_subtensor_w_int_and_matrix(self):
+        subt = self.ft4[0, :, self.ix2, :]
+        f = theano.function([self.ft4, self.ix2], subt, mode=self.mode)
+        ft4v = numpy.random.random((2, 3, 4, 5)).astype('float32')
+        ix2v = numpy.asarray([[0, 1], [1, 0]])
+        aval = f(ft4v, ix2v)
+        rval = ft4v[0, :, ix2v, :]
+        utt.assert_allclose(rval, aval)
+
     def test_inc_adv_subtensor_w_2vec(self):
         if inplace_increment is None:
             raise inplace_increment_missing