diff --git a/test/test_autograd.py b/test/test_autograd.py
index 53ddb8f67dccf7f..6e26f67f6dc34da 100644
--- a/test/test_autograd.py
+++ b/test/test_autograd.py
@@ -6795,6 +6795,20 @@ def inplace_double(x):
         # not leaf, not output
         test(lambda: (1 + torch.randn(5, requires_grad=True)), False)
 
+    def test_saved_variable_saved_original_inplace_detach(self):
+        # Detaching a tensor that is saved input raises
+        a = torch.tensor(1., requires_grad=True).clone()
+        b = a.sin()
+        a.detach_()
+        with self.assertRaisesRegex(RuntimeError, "Trying to use a saved tensor that has been detached"):
+            b.backward()
+
+        # Detaching a tensor that is saved as output is OK
+        a = torch.tensor(1., requires_grad=True).clone()
+        b = a.exp()
+        a.detach_()
+        b.backward()
+
     def test_saved_variable_packing_unpacking_did_not_save_original_with_hooks(self):
         # Tests that packing/unpacking a SavedVariable works correctly with user-defined hooks
         # The saved_original / did_not_save_original distinction corresponds to the `save_original`
diff --git a/torch/csrc/autograd/saved_variable.cpp b/torch/csrc/autograd/saved_variable.cpp
index a2e0f05b63943ba..d438205e8947fc8 100644
--- a/torch/csrc/autograd/saved_variable.cpp
+++ b/torch/csrc/autograd/saved_variable.cpp
@@ -144,7 +144,16 @@ Variable SavedVariable::unpack(std::shared_ptr<Node> saved_for) const {
                 : grad_fn_;
 
   if (!is_leaf_ && !grad_fn) {
-    TORCH_INTERNAL_ASSERT(saved_for, "No grad_fn for non-leaf saved tensor");
+    // This issue was introduced when we added logic to save the original
+    // because now we rely on data_.grad_fn(), but can be unreliable if the
+    // autograd_meta of that saved tensor is cleared with an in-place detach.
+    // As a simple fix, we choose to disallow that behavior here even though
+    // it makes behavior inconsistent depending on whether you are saving
+    // input or output.
+    TORCH_CHECK(
+        saved_for,
+        "Trying to use a saved tensor that has been detached in-place, i.e. with .detach_()."
+        "This is not supported, please use out-of-place `.detach()` instead");
     grad_fn = std::move(saved_for);
   }