Rename `do_not_clear` to `_do_not_clear` (#1977)

Signed-off-by: Jan Bielak <jbielak@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

transformer_engine/pytorch/cpu_offload.py

@@ -431,7 +431,7 @@ class AsyncDoubleBufferGroupOffloadHandler(SynchronizedGroupOffloadHandler):
             tensor = self.fp8_tensor_object_map.pop(tensor_tag)
 
         if self.double_buffering:
-            tensor.do_not_clear = True
+            tensor._do_not_clear = True
 
         self.tensor_tag_to_buf.pop(tensor_tag, None)
         # the tensor should have been copied back in on_group_commit_backward()

transformer_engine/pytorch/ops/fuser.py

@@ -101,7 +101,7 @@ class _OperationFuserAutogradFunction(torch.autograd.Function):
 
         # Mark input tensors as not deletable in backward
         for tensor in (input_,) + params_and_extra_inputs:
-            tensor.do_not_clear = True
+            tensor._do_not_clear = True
 
         # Unflatten list of parameters and extra tensor inputs
         extra_inputs = params_and_extra_inputs[-fuser.num_extra_inputs :]

transformer_engine/pytorch/utils.py

@@ -41,10 +41,10 @@ def clear_tensor_data(*tensors: Tuple[Optional[torch.Tensor], ...]) -> None:
     for t in tensors:
         if t is not None:
             # Workaround for double buffering in cpu offload
-            if hasattr(t, "do_not_clear"):
+            if hasattr(t, "_do_not_clear"):
                 continue
             if hasattr(t, "get_data_tensors"):
-                if any(hasattr(tensor, "do_not_clear") for tensor in t.get_data_tensors()):
+                if any(hasattr(tensor, "_do_not_clear") for tensor in t.get_data_tensors()):
                     continue
 
             if hasattr(t, "clear"):