Merge pull request #6044 from ReyhaneAskari/bye_bye_outputGaurd

theano/compile/debugmode.py

@@ -27,7 +27,8 @@ from theano.compile.function_module import (
     FunctionMaker, Function, infer_reuse_pattern,
     std_fgraph)
 from theano.compile.mode import Mode, register_mode
-from theano.compile.ops import OutputGuard
+from theano.compile.ops import OutputGuard, _output_guard
+
 
 __docformat__ = "restructuredtext en"
 _logger = logging.getLogger("theano.compile.debugmode")
@@ -2276,6 +2277,24 @@ class _Maker(FunctionMaker):  # inheritance buys a few helper functions
                               "of", len(li), "events was stable.",
                               file=sys.stderr)
         self.fgraph = fgraph
+        destroy_handler_added = False
+        for feature in fgraph._features:
+            if isinstance(feature, gof.DestroyHandler):
+                destroy_handler_added = True
+                break
+        if not destroy_handler_added:
+            fgraph.attach_feature(gof.DestroyHandler())
+        for o in fgraph.outputs:
+            try:
+                fgraph.replace_validate(o, _output_guard(o), reason='output_guard')
+                raise Exception("Output variable %s required output_guard, "
+                                "how was this output left unprotected against "
+                                "destructive operations?" % o)
+
+            except gof.InconsistencyError:
+                # This output is already impossible to destroy.
+                # No guard necessary
+                pass
 
         linker = _Linker(self)
 

theano/compile/function_module.py

@@ -18,7 +18,6 @@ import theano
 from theano import config, gof
 from theano.compat import izip
 from theano.gof import graph
-import theano.compile.mode
 import theano.compile.profiling
 from theano.compile.io import (
     In, SymbolicInput, SymbolicOutput)

theano/compile/mode.py

@@ -4,13 +4,14 @@ WRITEME
 """
 from __future__ import absolute_import, print_function, division
 import logging
+import warnings
 
 import theano
 from theano import gof
 import theano.gof.vm
 from theano.configparser import config
-from theano.compile.ops import _output_guard
 from six import string_types
+from theano.compile.function_module import Supervisor
 
 
 _logger = logging.getLogger('theano.compile.mode')
@@ -111,18 +112,16 @@ class AddDestroyHandler(gof.Optimizer):
 
     """
     def apply(self, fgraph):
-        for o in fgraph.outputs:
-            try:
-                fgraph.replace_validate(o, _output_guard(o),
-                                        reason='output_guard')
-                _logger.info("Output variable %s required output_guard, "
-                             "how was this output left unprotected against "
-                             "destructive operations?"
-                             % o)
-            except gof.InconsistencyError:
-                # This output is already impossible to destroy.
-                # No guard necessary
-                pass
+        supervisor_added = False
+        for feature in fgraph._features:
+            if isinstance(feature, Supervisor):
+                supervisor_added = True
+                break
+        if not supervisor_added:
+            warnings.warn("WARNING: Supervisor is not added. Please build a FunctionGraph"
+                          "via theano.compile.function_module.std_graph()"
+                          "or add the Supervisor class manually.",
+                          stacklevel=3)
 
     def add_requirements(self, fgraph):
         super(AddDestroyHandler, self).add_requirements(fgraph)

theano/tensor/basic.py

@@ -447,6 +447,8 @@ def get_scalar_constant_value(orig_v, elemwise=True,
                 max_recur > 0):
             max_recur -= 1
             if isinstance(v.owner.op, (Alloc, DimShuffle, Rebroadcast,
+                                       # outputguard is only used in debugmode but we
+                                       # keep it here to avoid problems with old pickels.
                                        compile.ops.OutputGuard,
                                        compile.DeepCopyOp)):
                 v = v.owner.inputs[0]

theano/tensor/nnet/tests/test_nnet.py

@@ -579,8 +579,7 @@ class T_CrossentropyCategorical1Hot(utt.InferShapeTester):
         theano.compile.mode.optdb.query(
             theano.compile.mode.OPT_FAST_RUN).optimize(fgraph)
 
-        assert str(fgraph.outputs[0].owner.op) == 'OutputGuard'
-        assert (fgraph.outputs[0].owner.inputs[0].owner.op ==
+        assert (fgraph.outputs[0].owner.op ==
                 crossentropy_softmax_argmax_1hot_with_bias)
 
     def test_softmax_optimizations_vector(self):
@@ -594,8 +593,7 @@ class T_CrossentropyCategorical1Hot(utt.InferShapeTester):
 
         theano.compile.mode.optdb.query(
             theano.compile.mode.OPT_FAST_RUN).optimize(fgraph)
-        assert str(fgraph.outputs[0].owner.op) == 'OutputGuard'
-        assert (fgraph.outputs[0].owner.inputs[0].owner.op ==
+        assert (fgraph.outputs[0].owner.op ==
                 crossentropy_softmax_argmax_1hot_with_bias)
 
     def test_softmax_optimizations_w_bias(self):
@@ -624,10 +622,8 @@ class T_CrossentropyCategorical1Hot(utt.InferShapeTester):
         #    print node.op
         # print printing.pprint(node.outputs[0])
         # print '===='
-        assert len(fgraph.toposort()) == 2
-
-        assert str(fgraph.outputs[0].owner.op) == 'OutputGuard'
-        assert (fgraph.outputs[0].owner.inputs[0].owner.op ==
+        assert len(fgraph.toposort()) == 1
+        assert (fgraph.outputs[0].owner.op ==
                 crossentropy_softmax_argmax_1hot_with_bias)
 
     def test_softmax_optimizations_w_bias2(self):
@@ -654,10 +650,9 @@ class T_CrossentropyCategorical1Hot(utt.InferShapeTester):
         # for node in fgraph.toposort():
         #    print node.op
         # print '===='
-        assert len(fgraph.toposort()) == 3
+        assert len(fgraph.toposort()) == 2
 
-        assert str(fgraph.outputs[0].owner.op) == 'OutputGuard'
-        assert (fgraph.outputs[0].owner.inputs[0].owner.op ==
+        assert (fgraph.outputs[0].owner.op ==
                 crossentropy_softmax_argmax_1hot_with_bias)
 
     def test_softmax_optimizations_w_bias_vector(self):
@@ -681,9 +676,8 @@ class T_CrossentropyCategorical1Hot(utt.InferShapeTester):
         # for node in fgraph.toposort():
         #    print node.op
         # print '===='
-        assert len(fgraph.toposort()) == 3
-        assert str(fgraph.outputs[0].owner.op) == 'OutputGuard'
-        assert (fgraph.outputs[0].owner.inputs[0].owner.op ==
+        assert len(fgraph.toposort()) == 2
+        assert (fgraph.outputs[0].owner.op ==
                 crossentropy_softmax_argmax_1hot_with_bias)
 
     def test_softmax_grad_optimizations(self):
@@ -1338,9 +1332,8 @@ def test_argmax_pushdown():
         # print 'AFTER'
         # for node in fgraph.toposort():
         # print node.op
-        assert len(fgraph.toposort()) == 2  # an output_guard is second
+        assert len(fgraph.toposort()) == 1
         assert fgraph.toposort()[0].op == tensor.basic._argmax
-        assert str(fgraph.toposort()[1].op) == 'OutputGuard'
         assert check_stack_trace(
             fgraph, ops_to_check=tensor.basic._argmax)
         x = tensor.matrix()
@@ -1364,12 +1357,11 @@ def test_argmax_pushdown():
         # print 'AFTER'
         # for node in fgraph.toposort():
             # print node.op
-        assert len(fgraph.toposort()) == 4  # an output_guard is second
+        assert len(fgraph.toposort()) == 3
         assert isinstance(fgraph.toposort()[0].op, tensor.Elemwise)
         assert isinstance(fgraph.toposort()[1].op, Softmax)
         assert isinstance(fgraph.toposort()[2].op, tensor.CAReduce)
         assert isinstance(fgraph.toposort()[2].op.scalar_op, theano.scalar.Maximum)
-        assert str(fgraph.toposort()[3].op) == 'OutputGuard'
 
 
 def test_argmax_pushdown_bias():
@@ -1388,10 +1380,9 @@ def test_argmax_pushdown_bias():
     # for node in fgraph.toposort():
     #    print node.op
     types_to_check = (tensor.DimShuffle, tensor.Elemwise, tensor.Argmax)
-    assert len(fgraph.toposort()) == 4
+    assert len(fgraph.toposort()) == 3
     for i, type in enumerate(types_to_check):
         assert isinstance(fgraph.toposort()[i].op, type)
-    assert str(fgraph.toposort()[3].op) == 'OutputGuard'
     assert check_stack_trace(fgraph, ops_to_check=types_to_check)
 
     x = tensor.matrix()
@@ -1412,11 +1403,10 @@ def test_argmax_pushdown_bias():
     # print 'AFTER'
     # for node in fgraph.toposort():
     #    print node.op
-    assert len(fgraph.toposort()) == 3
+    assert len(fgraph.toposort()) == 2
     assert isinstance(fgraph.toposort()[0].op, SoftmaxWithBias)
     assert isinstance(fgraph.toposort()[1].op, tensor.CAReduce)
     assert isinstance(fgraph.toposort()[1].op.scalar_op, theano.scalar.Maximum)
-    assert str(fgraph.toposort()[2].op) == 'OutputGuard'
     assert check_stack_trace(
         fgraph, ops_to_check=(SoftmaxWithBias, tensor.CAReduce))