Merge pull request #2338 from abergeron/set_to_inc

theano/tensor/opt.py

@@ -29,7 +29,8 @@ from theano.tensor.subtensor import (get_idx_list, get_canonical_form_slice,
                                      Subtensor, IncSubtensor, make_constant,
                                      AdvancedIncSubtensor1,
                                      AdvancedIncSubtensor,
-                                     AdvancedSubtensor1)
+                                     AdvancedSubtensor1,
+                                     advanced_inc_subtensor1)
 from theano import scalar
 from theano.tensor import basic as T
 from theano import compile  # to register the optimizer built by this file
@@ -1345,10 +1346,10 @@ def local_subtensor_make_vector(node):
     replace all subtensor(make_vector) like:
     [a,b,c][0] -> a
     [a,b,c][0:2] -> [a,b]
-    
+
     replace all AdvancedSubtensor1(make_vector) like:
     [a,b,c][[0,2]] -> [a,c]
-    
+
     we can do this for constant indexes
     """
     x = node.inputs[0]
@@ -1629,13 +1630,13 @@ def local_elemwise_alloc(node):
     if len(node.outputs) > 1:
         # Ensure all outputs have the same broadcast pattern
         # This is a supposition that I'm not sure is always true.
-        assert all([o.type.broadcastable == 
+        assert all([o.type.broadcastable ==
                     node.outputs[0].type.broadcastable for o in
                     node.outputs[1:]])
 
     # The broadcast pattern of the ouptut must match the broadcast pattern of
     # at least one of the inputs.
-    if not any([i.type.broadcastable == 
+    if not any([i.type.broadcastable ==
         node.outputs[0].type.broadcastable for i in node.inputs]):
         return False
 
@@ -1874,6 +1875,38 @@ def local_useless_inc_subtensor(node):
         return [Subtensor(node.op.idx_list)(*node.inputs[1:])]
 
 
+@register_canonicalize
+@gof.local_optimizer([AdvancedIncSubtensor1])
+def local_set_to_inc_subtensor(node):
+    """
+    AdvancedIncSubtensor1(x, x[ilist]+other, ilist, set_instead_of_inc=True) ->
+    AdvancedIncSubtensor1(x, other, ilist, set_instead_of_inc=False)
+    """
+    if (isinstance(node.op, AdvancedIncSubtensor1) and
+        node.op.set_instead_of_inc == True and
+        node.inputs[1].owner and
+        isinstance(node.inputs[1].owner.op, Elemwise) and
+        isinstance(node.inputs[1].owner.op.scalar_op, scalar.Add)):
+        addn = node.inputs[1].owner
+        subn = None
+        other = None
+
+        if (addn.inputs[0].owner and
+            isinstance(addn.inputs[0].owner.op, AdvancedSubtensor1)):
+            subn = addn.inputs[0].owner
+            other = addn.inputs[1]
+        elif (addn.inputs[1].owner and
+              isinstance(addn.inputs[1].owner.op, AdvancedSubtensor1)):
+            subn = addn.inputs[1].owner
+            other = addn.inputs[0]
+        else:
+            return
+        if (subn.inputs[1] != node.inputs[2] or
+            subn.inputs[0] != node.inputs[0]):
+            return
+        return [advanced_inc_subtensor1(node.inputs[0], other, node.inputs[2])]
+
+
 @register_canonicalize
 @register_specialize
 @gof.local_optimizer([Subtensor])

theano/tensor/tests/test_opt.py

@@ -2697,6 +2697,35 @@ def test_local_IncSubtensor_serialize():
                         for inp in a.inputs])
 
 
+def test_local_set_to_inc_subtensor():
+    v = theano.tensor.fmatrix()
+    s = v[[2, 1]]
+    g = s + 3
+    r = theano.tensor.set_subtensor(s, g)
+    moder = compile.get_default_mode().excluding('local_set_to_inc_subtensor')
+    modet = compile.get_default_mode().including('local_set_to_inc_subtensor')
+    f1 = theano.function([v], r, mode=moder)
+    f2 = theano.function([v], r, mode=modet)
+
+    advi1 = [n for n in f1.maker.fgraph.toposort()
+             if isinstance(n.op, tensor.AdvancedIncSubtensor1)]
+
+    advi2 = [n for n in f2.maker.fgraph.toposort()
+             if isinstance(n.op, tensor.AdvancedIncSubtensor1)]
+
+    # We only have SetSubtensor in f1
+    assert all(n.op.set_instead_of_inc for n in advi1)
+    # We don't have any SetSubtensor in f2
+    assert all(not n.op.set_instead_of_inc for n in advi2)
+
+    val = numpy.random.randn(3, 2).astype('float32')
+
+    r1 = f1(val)
+    r2 = f2(val)
+
+    utt.assert_allclose(r1, r2)
+
+
 def test_local_subtensor_of_dot():
     m1 = theano.tensor.matrix()
     m2 = theano.tensor.matrix()