More work on issue #3018.

theano/tensor/tests/test_opt.py

@@ -4027,6 +4027,10 @@ class T_Tile(unittest.TestCase):
                 assert isinstance(topo[0].op, compile.DeepCopyOp)
                 f(data)
                 
+                # Check that stacktrace is copied over
+                self.assertTrue(hasattr(f.outputs[0].variable.tag, 'trace'))
+                self.assertTrue(len(f.outputs[0].variable.tag.trace)>0)
+
 
 def speed_local_pow_specialize_range():
     val = numpy.random.rand(1e7)
@@ -5711,6 +5715,7 @@ def test_local_join_empty():
                 for n in e if isinstance(n.op, Join)])
     assert f.maker.fgraph.outputs[0].dtype == config.floatX
 
+
     # test for matrix join(1,a)
     empty_mat = numpy.asarray([[]], dtype=config.floatX)
     m = tensor.matrix('m')
@@ -5723,7 +5728,6 @@ def test_local_join_empty():
     assert all([not isinstance(n.op, Join) or len(n.inputs) == 4
                 for n in e if isinstance(n.op, Join)])
     assert f.maker.fgraph.outputs[0].dtype == config.floatX
-
     # test for vector, vector, empty to matrix
     # We can't optimize this case.
     s = tensor.stack([a, a, empty_vec])
@@ -5735,7 +5739,6 @@ def test_local_join_empty():
     assert all([not isinstance(n.op, Join) or len(n.inputs) == 4
                 for n in e if isinstance(n.op, Join)])
     assert f.maker.fgraph.outputs[0].dtype == config.floatX
-
     # test for matrix join(0,a)
     # We can't optimize this case.
     s = join(0, m, numpy.asarray([[2.]], dtype=config.floatX), m)
@@ -5748,6 +5751,20 @@ def test_local_join_empty():
                 for n in e if isinstance(n.op, Join)])
     assert f.maker.fgraph.outputs[0].dtype == config.floatX
     
+    # Julian: we can enable the following test, once we 
+    # remove default optimizations.
+    # When we set optimizer=None, no optimizations should be applied,
+    # but that's not the case now...
+    
+    # test that optimizations keep stack trace
+    #mode = theano.compile.mode.Mode(optimizer=None).including('canonicalize_db').including("local_join_empty")
+    #empty_mat = numpy.asarray([[]], dtype=config.floatX)
+    #m = tensor.matrix('m')
+    #s = join(1, empty_mat, m, m, m)
+    #f = function([m], s, mode=mode)
+    #assert hasattr(f.outputs[0].variable.tag, 'trace')
+    #assert len(f.outputs[0].variable.tag.trace) > 0
+
 
 def test_local_join_make_vector():
     a, b, c, d, e = tensor.scalars('abcde')
@@ -5765,6 +5782,10 @@ def test_local_join_make_vector():
     assert f.maker.fgraph.outputs[0].dtype == config.floatX
 
 
+    print(f.outputs[0].variable.tag)
+    print(f.outputs[0].variable.tag.trace)
+
+
 def test_local_add_specialize():
     # test of non-zero dimension
     a = tensor.vector()
@@ -5864,6 +5885,12 @@ def test_local_useless_split():
     assert len(graph_nonopt)==1
     assert isinstance(graph_nonopt[0].op, tensor.Split)
 
+    # Check that stacktraces have been copied over properly
+    assert hasattr(f_opt.outputs[0].variable.tag, 'trace')
+    assert len(f_opt.outputs[0].variable.tag.trace) > 0
+    assert hasattr(f_nonopt.outputs[0].variable.tag, 'trace')
+    assert len(f_nonopt.outputs[0].variable.tag.trace) > 0
+
 
 def test_local_flatten_lift():
     for i in xrange(1, 4):