Return the updated inp from seteitem_

The following trace
```
def higher_order_autograd_function_apply_brtuu(any5, t_0, t_1):
  # <eval_with_key>.83:5:           _set_grad_enabled = torch._C._set_grad_enabled(False);  _set_grad_enabled = None
  ltorch._set_grad_enabled_with_warning(False)

  # <eval_with_key>.83:6:           output = torch.zeros(4096, 32, 128, device = device(type='cuda', index=0), dtype = torch.bfloat16)
  t2 = ltorch.zeros(4096, 32, 128, device=devices.Device("cuda:0"), dtype=torch.bfloat16)  # t2: "cuda:0 bf16[4096, 32, 128] self._requires_grad=False"
    # t2 = ltorch.full((4096, 32, 128), 0, device=devices.Device("cuda:0"), dtype=torch.bfloat16)  # t2: "cuda:0 bf16[4096, 32, 128] self._requires_grad=False"
      # t2 = prims.full((4096, 32, 128), 0, device=devices.Device("cuda:0"), dtype=dtypes.bfloat16)  # t2: "cuda:0 bf16[4096, 32, 128] self._requires_grad=False"

  # <eval_with_key>.83:8:           _set_grad_enabled_1 = torch._C._set_grad_enabled(True);  _set_grad_enabled_1 = None
  (t0,) = prims.update_aliases((t2,))
  t4 = ltorch.setitem_(t0, t_1, t_0)  # t4: "cuda:0 bf16[4096, 32, 128] self._requires_grad=False"
    # t3 = ltorch.setitem(t0, t_1, t_0)  # t3: "cuda:0 bf16[4096, 32, 128] self._requires_grad=False"
      # t3 = prims.copy_with_setitem(t0, t_1, t_0)  # t3: "cuda:0 bf16[4096, 32, 128] self._requires_grad=False"
    # t4 = prims.copy_(t3, t0, grad_enabled=False)  # t4: "cuda:0 bf16[4096, 32, 128] self._requires_grad=False"
  ltorch._set_grad_enabled_with_warning(True)
  return (t4, [t_1])
```
seems to return `None` inside
https://github.com/Lightning-AI/lightning-thunder/blob/a7952e29bae925581d3bf7069d64386f4d888e00/thunder/core/jit_ext.py#L998-L1007
of `_general_jit_torch_ops_higher_order_autograd_function_apply` and the
cause seems to be that `ltorch.setitem_` has been a void function.

Signed-off-by: Masaki Kozuki <mkozuki@nvidia.com>

Author: crcrpar

thunder/torch/__init__.py

@@ -1141,7 +1141,7 @@ def setitem(inp, idx, val):
 
 @torchsymbol(torch.Tensor.__setitem__, id="setitem_", is_method=True, tags=(prims.OpTags.IN_PLACE,))
 def setitem_(inp, idx, val):
-    _copy_(inp, setitem(inp, idx, val))
+    return _copy_(inp, setitem(inp, idx, val))
 
 
 @torchsymbol(torch.Tensor.__getitem__, id="torch.Tensor.__getitem__", method_name="getitem")