Merge pull request #314 from bayerj/feature-AdvancedIncSubtensor-grad

theano/tensor/basic.py

@@ -5139,10 +5139,14 @@ class AdvancedIncSubtensor(Op):
         out[0] = inputs[0].copy()
         out[0][inputs[2:]] += inputs[1]
 
-    #def grad?
-        # grad on x is grad  on output
-        # grad on y is grad_output[idx_list]
-        # grad on rest is None
+    def grad(self, inpt, output_gradients):
+        x, y = inpt[:2]
+        idxs = inpt[2:]
+        outgrad, = output_gradients
+        d_x_wrt_C = outgrad
+        d_y_wrt_C = AdvancedSubtensor(self.args)(outgrad, *idxs)
+        return [d_x_wrt_C, d_y_wrt_C] + [None for _ in idxs]
+
     def R_op(self, inputs, eval_points):
         if None in eval_points[:2]:
             return [None]

theano/tensor/tests/test_basic.py

@@ -2605,6 +2605,32 @@ class T_subtensor(unittest.TestCase):
             val = f()
             self.assertTrue(numpy.allclose(val, data[idx].shape))
 
+    def test_grad_advanced_inc_subtensor(self):
+        def inc_slice(*s):
+            def just_numeric_args(a,b):
+                cost = (a[s] + b).sum()
+                cost_wrt_a = grad(cost, a)
+                cost_wrt_b = grad(cost, b)
+                grads = cost_wrt_a.sum() + cost_wrt_b.sum()
+                return grads
+            return just_numeric_args
+
+        # vector
+        utt.verify_grad(
+            inc_slice(slice(2, 4, None)),
+            (numpy.asarray([0, 1, 2, 3, 4, 5.]), numpy.asarray([9, 9.]),))
+
+        # matrix
+        utt.verify_grad(
+            inc_slice(slice(1, 2, None), slice(None, None, None)),
+            (numpy.asarray([[0, 1], [2, 3], [4, 5.]]),
+             numpy.asarray([[9, 9.]]),))
+
+        #single element
+        utt.verify_grad(
+            inc_slice(2, 1),
+            (numpy.asarray([[0, 1],[2, 3],[4, 5.]]), numpy.asarray(9.),))
+
 
 class TestIncSubtensor1(unittest.TestCase):
     # test inc_subtensor

theano/tensor/tests/test_inc_subtensor.py

@@ -87,6 +87,7 @@ class Test_inc_subtensor(unittest.TestCase):
                 expected_result[:,sl3,:val_sl2_end] += val_inc
 
             self.assertTrue(numpy.array_equal(result, expected_result))
+
     def test_grad_inc_set(self):
         def inc_slice(*s):
             def just_numeric_args(a,b):
@@ -116,3 +117,4 @@ class Test_inc_subtensor(unittest.TestCase):
                     f_slice(2, 1),
                     (numpy.asarray([[0,1],[2,3],[4,5.]]),
                         numpy.asarray(9.),))
+