Preserv the nan_guard_mode_check

theano/compile/function_module.py

@@ -199,7 +199,7 @@ def std_fgraph(input_specs, output_specs, accept_inplace=False):
     return fgraph, list(map(SymbolicOutput, updates))
 
 
-std_fgraph.features = [gof.toolbox.PreserveNames]
+std_fgraph.features = [gof.toolbox.PreserveVariableAttributes]
 
 
 class AliasedMemoryError(Exception):

theano/compile/nanguardmode.py

@@ -323,7 +323,7 @@ class NanGuardMode(Mode):
             fn()
             outputs = fn.outputs
             for x, var in zip(outputs, node.outputs):
-                if getattr(var, 'nan_guard_mode_check', True):
+                if getattr(var.tag, 'nan_guard_mode_check', True):
                     do_check_on(x[0], node, fn, False)
 
         wrap_linker = theano.gof.WrapLinker([theano.gof.OpWiseCLinker()],

theano/gof/toolbox.py

@@ -454,11 +454,17 @@ class PrintListener(Feature):
                 node, i, r, new_r))
 
 
-class PreserveNames(Feature):
+class PreserveVariableAttributes(Feature):
+    """
+    This preserve some variables attributes and tag during optimization.
+    """
 
     def on_change_input(self, fgraph, node, i, r, new_r, reason=None):
         if r.name is not None and new_r.name is None:
             new_r.name = r.name
+        if getattr(r.tag, 'nan_guard_mode_check', False) and getattr(
+                new_r.tag, 'nan_guard_mode_check', False) is False:
+            new_r.tag.nan_guard_mode_check = r.tag.nan_guard_mode_check
 
 
 class NoOutputFromInplace(Feature):

theano/scan_module/scan_utils.py

@@ -621,7 +621,7 @@ def expand_empty(tensor_var, size):
     empty = tensor.AllocEmpty(tensor_var.dtype)(*new_shape)
 
     ret = tensor.set_subtensor(empty[:shapes[0]], tensor_var)
-    ret.nan_guard_mode_check = False
+    ret.tag.nan_guard_mode_check = False
     return ret
 
 

theano/tensor/basic.py

@@ -6242,7 +6242,9 @@ class AllocEmpty(gof.Op):
         # We can't reuse filter_checks_isfinite as by default it is
         # False and it is set to true only in DebugMode.
         # We can't set it in the type as other make_node can reuse the type.
-        output.nan_guard_mode_check = False
+        # We can't set it in the variable as it isn't copied when we copy
+        # the variale. So we set it in the tag.
+        output.tag.nan_guard_mode_check = False
         return Apply(self, shape, [output])
 
     def perform(self, node, inputs, out_):

theano/tensor/opt.py

@@ -3076,9 +3076,6 @@ def local_inplace_setsubtensor(node):
             set_instead_of_inc=node.op.set_instead_of_inc,
             destroyhandler_tolerate_aliased=dta)
         new_node = new_op(*node.inputs)
-        # Keep the information needed for NanGuardMode.
-        new_node.nan_guard_mode_check = getattr(
-            node.op, 'nan_guard_mode_check', True)
         # Copy stacktrace from original outputs to new outputs.
         # This is sensible, because the new operation is the
         # same as the old one, but now with different attributes.