diff --git a/test/test_autograd.py b/test/test_autograd.py
index 671ebc449de4d..10e8ad4096921 100644
--- a/test/test_autograd.py
+++ b/test/test_autograd.py
@@ -7021,6 +7021,32 @@ def run_tests(fn):
         run_tests(lambda v: v.swapdims_(0, 0))
         run_tests(lambda v: v.swapaxes_(0, 0))
 
+    def test_autograd_print_tensor(self):
+        a = torch.ones(1, requires_grad=True)
+        a_clone = a.clone()
+        self.assertEqual(repr(a), "tensor([1.], requires_grad=True)")
+        self.assertEqual(repr(a_clone), "tensor([1.], grad_fn=<CloneBackward0>)")
+
+        with torch.no_grad():
+            b = a[:]
+            b *= 2
+
+        # Special handling for printing view created in no-grad and modified
+        # in-placed in no-grad.
+        self.assertEqual(repr(b), "tensor([2.], grad_fn=<Invalid>)")
+
+        class Func(torch.autograd.Function):
+            @staticmethod
+            def forward(ctx, x):
+                return x
+
+            @staticmethod
+            def backward(ctx, x):
+                return x
+
+        c = Func.apply(a)
+        self.assertEqual(repr(c), "tensor([2.], grad_fn=<FuncBackward>)")
+
     def test_autograd_inplace_view_of_view(self):
         x = torch.zeros(2)
         with torch.no_grad():
diff --git a/torch/_tensor_str.py b/torch/_tensor_str.py
index 364149e7bb7e5..1293a0fd61aec 100644
--- a/torch/_tensor_str.py
+++ b/torch/_tensor_str.py
@@ -601,11 +601,22 @@ def indented_str(s, indent):
 
     # Use inp here to get the original grad_fn and not the one generated by the forward grad
     # unpacking.
-    if inp.grad_fn is not None:
-        name = type(inp.grad_fn).__name__
-        if name == "CppFunction":
-            name = inp.grad_fn.name().rsplit("::", 1)[-1]
-        suffixes.append(f"grad_fn=<{name}>")
+    grad_fn_name = None
+    try:
+        grad_fn = inp.grad_fn
+    except RuntimeError:
+        # Accessing the grad_fn calls rebasing logic which would cause an error
+        # if that tensor is a view created in no-grad mode modified in-place in
+        # no-grad mode. See: https://github.com/pytorch/pytorch/issues/99968
+        grad_fn_name = "Invalid"
+
+    if grad_fn_name is None and grad_fn is not None:
+        grad_fn_name = type(grad_fn).__name__
+        if grad_fn_name == "CppFunction":
+            grad_fn_name = grad_fn.name().rsplit("::", 1)[-1]
+
+    if grad_fn_name is not None:
+        suffixes.append(f"grad_fn=<{grad_fn_name}>")
     elif inp.requires_grad:
         suffixes.append("requires_grad=True")