inductor `compile_fx_inner` output is incorrect on graph with trailing copy_()
Labels: triaged, module: inductor

Repro here:
```
import torch
from torch._inductor.compile_fx import compile_fx_inner
from torch.fx.experimental.proxy_tensor import make_fx

def f(arg0_1):
    slice_1 = torch.ops.aten.slice.Tensor(arg0_1, 0, 0)
    slice_2 = torch.ops.aten.slice.Tensor(slice_1, 1, 20, 40)
    add = torch.ops.aten.add.Tensor(slice_2, 1)
    slice_3 = torch.ops.aten.slice.Tensor(arg0_1, 0, 0)
    slice_4 = torch.ops.aten.slice.Tensor(slice_3, 1, 20, 40)
    slice_5 = torch.ops.aten.slice.Tensor(arg0_1, 0, 0)
    slice_scatter = torch.ops.aten.slice_scatter.default(slice_5, add, 1, 20, 40)
    slice_scatter_1 = torch.ops.aten.slice_scatter.default(arg0_1, slice_scatter, 0, 0)
    slice_6 = torch.ops.aten.slice.Tensor(slice_scatter_1, 0, 0)
    slice_7 = torch.ops.aten.slice.Tensor(slice_6, 1, 20, 40)
    slice_8 = torch.ops.aten.slice.Tensor(arg0_1, 0, 0)
    slice_9 = torch.ops.aten.slice.Tensor(slice_8, 1, 1, 10)
    slice_10 = torch.ops.aten.slice.Tensor(slice_scatter_1, 0, 0)
    slice_11 = torch.ops.aten.slice.Tensor(slice_10, 1, 1, 10)
    add_1 = torch.ops.aten.add.Tensor(slice_11, 2)
    slice_12 = torch.ops.aten.slice.Tensor(arg0_1, 0, 0)
    slice_13 = torch.ops.aten.slice.Tensor(slice_12, 1, 2, 11)
    slice_14 = torch.ops.aten.slice.Tensor(slice_scatter_1, 0, 0)
    slice_15 = torch.ops.aten.slice.Tensor(slice_14, 1, 2, 11)
    slice_16 = torch.ops.aten.slice.Tensor(slice_scatter_1, 0, 0)
    slice_scatter_2 = torch.ops.aten.slice_scatter.default(slice_16, add_1, 1, 2, 11)
    slice_scatter_3 = torch.ops.aten.slice_scatter.default(slice_scatter_1, slice_scatter_2, 0, 0)
    slice_17 = torch.ops.aten.slice.Tensor(slice_scatter_3, 0, 0)
    slice_18 = torch.ops.aten.slice.Tensor(slice_17, 1, 2, 11)
    copy_ = torch.ops.aten.copy_.default(arg0_1, slice_scatter_3)
    return ()

x_ref = torch.ones([1, 64], device='cpu')
x_test = torch.ones([1, 64], device='cpu')
x_test2 = torch.ones([1, 64], device='cpu')
x_test3 = torch.ones([1, 64], device='cpu')

fx_g = make_fx(f)(x_test2)
f_compiled = compile_fx_inner(fx_g, [x_test3])

f(x_ref)
f_compiled([x_test])

print(x_test)
print(torch.abs(x_test - x_ref))
# Prints False
print(torch.allclose(x_test, x_ref))

```

The repro is a bit cumbersome, but it comes from the functionalized version of this test ([code](https://github.com/pytorch/pytorch/blob/54c0f37646b8e7483519c4246a826ea7cbc6f695/test/inductor/test_torchinductor.py#L4032)).

I bisected it to this commit: https://github.com/pytorch/pytorch/pull/94110. Strangely, it only seems to fail on cpu and not on inductor's cuda backend.

I noticed this error due to my changes to functionalize the inference graph in AOTAutograd, which appends trailing copy_() calls to the graph before sending them to inductor when there are input mutations. There are existing failures in https://github.com/pytorch/pytorch/pull/92857

cc @mlazos @soumith @voznesenskym @yanboliang @penguinwu @anijain2305 @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @Xia-Weiwen @wenzhe-nrv @jiayisunx @peterbell10 @desertfire