Merge pull request #4 from nouiz/lamblin-fix_inc_set_subtensor1

theano/tensor/subtensor.py

@@ -1119,8 +1119,13 @@ def inc_subtensor(x, y, inplace=False, set_instead_of_inc=False,
         # We also explicitly duplicate y to its broadcasted shape
         # before we partially flatten it to inner_x dimension. This is
         # not strictly needed in all cases, but it is easier this way.
-        expanded_y = alloc(y, *[x.shape[i] for i in range(x.ndim)])
-        flattened_y = expanded_y.flatten(inner_x.ndim)
+        if y.ndim > 0:
+            # This if is needed to prevent some useless warning about
+            # old code bug.
+            expanded_y = alloc(y, *[x.shape[i] for i in range(x.ndim)])
+            flattened_y = expanded_y.flatten(inner_x.ndim)
+        else:
+            flattened_y = y
 
         # Warn if this code path would have produced wrong results in the past
         if config.warn.inc_set_subtensor1:

theano/tensor/tests/test_subtensor.py

@@ -1035,15 +1035,8 @@ class T_subtensor(unittest.TestCase, utt.TestOptimizationMixin):
         m = matrix('m')
         i = lmatrix('i')
 
-        # That test actually gave correct results, the warning is
-        # a bit too broad
-        orig_warn = config.warn.inc_set_subtensor1
-        try:
-            config.warn.inc_set_subtensor1 = False
-            m1 = set_subtensor(m[:, i], 0)
-            m2 = inc_subtensor(m[:, i], 1)
-        finally:
-            config.warn.inc_set_subtensor1 = orig_warn
+        m1 = set_subtensor(m[:, i], 0)
+        m2 = inc_subtensor(m[:, i], 1)
 
         f = theano.function([m, i], [m1, m2])
 
@@ -1060,10 +1053,10 @@ class T_subtensor(unittest.TestCase, utt.TestOptimizationMixin):
         assert numpy.allclose(m1_val, m1_ref), (m1_val, m1_ref)
         assert numpy.allclose(m2_val, m2_ref), (m2_val, m2_ref)
 
-    def test_adv1_inc_sub_notlastdim_1dval(self):
+    def test_adv1_inc_sub_notlastdim_1_2dval_broadcast(self):
         # Test that taking 1-dimensional advanced indexing
         # over a dimension that's not the first (outer-most),
-        # and incrementing/setting a 1D value works.
+        # and incrementing/setting with broadcast
         m = matrix('m')
 
         # Test for both vector and matrix as index
@@ -1097,16 +1090,16 @@ class T_subtensor(unittest.TestCase, utt.TestOptimizationMixin):
         finally:
             config.warn.inc_set_subtensor1 = orig_warn
 
-    def test_adv1_inc_sub_notlastdim_2dval(self):
+    def test_adv1_inc_sub_notlastdim_1_2dval_no_broadcast(self):
         # Test that taking 1-dimensional advanced indexing
         # over a dimension that's not the first (outer-most),
-        # and incrementing/setting a 2D value works.
+        # and incrementing/setting without broadcast
         m = matrix('m')
 
         # Test for both vector and matrix as index
         sym_i = (lvector('i'), lmatrix('i'))
         shape_i = ((4,), (4, 2))
-        shape_val = ((3, 1), (3, 1, 1))
+        shape_val = ((3, 4), (3, 4, 2))
 
         # Disable the warning emitted for that case
         orig_warn = config.warn.inc_set_subtensor1