Repository: pytorch
Issue: [Bug][CompiledAutograd] PyTorch with CompiledAutograd throws an IndexError: list index out of range when the hook code includes a list append operation.
Labels: triaged,oncall: pt2,module: dynamo,module: compiled autograd

### 🐛 Describe the bug

There is an issue with tracing hooks when the hook contains list append operations (it also depends on which element is added; for example, adding an integer causes no issue). This seems to occur in certain corner cases, one of which is provided below. However, if I change the line grads.append(grad) to something like grads.append(0), the issue doesn't occur.
```python 
import torch
import torch._dynamo.utils
from torch._dynamo import compiled_autograd

def test_compiled_autograd():
        device = "cpu"
        backend = "inductor"

        grads = []
        
        def hook_fn(grad):
            #If the line below is commented out or changed to, for example, grads.append(grad), there is no issue
            grads.append(grad)
            return grad
        
        def fn(x, y):
            x.register_hook(hook_fn)
            return x + y
        
        def compiler_fn(gm):
            return torch.compile(gm, backend=backend)

        torch._dynamo.reset()
    
        with compiled_autograd.enable(compiler_fn):
            x = torch.tensor([0.5, 0.5], device=device, requires_grad=True)
            y = torch.tensor([0.5, 0.5], device=device, requires_grad=True)
            out = fn(x, y)
            grad_out = torch.tensor([2.0, 2.0], device=device)
            out.backward(grad_out)

test_compiled_autograd()
```
Traceback below
```
Traceback (most recent call last):
  File "/lib/python3.10/site-packages/torch/fx/graph_module.py", line 303, in __call__
    return super(self.cls, obj).__call__(*args, **kwargs)  # type: ignore[misc]
  File "/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1556, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1565, in _call_impl
    return forward_call(*args, **kwargs)
  File "<eval_with_key>.2", line 4, in forward
    def forward(self, inputs, sizes, hooks):
IndexError: list index out of range

Call using an FX-traced Module, line 4 of the traced Module's generated forward function:

def forward(self, inputs, sizes, hooks):

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
    getitem = inputs[0]

    getitem_1 = inputs[1]

Traceback (most recent call last):
  File "/src/test.py", line 35, in <module>
    test_compiled_autograd()
  File "/src/test.py", line 33, in test_compiled_autograd
    out.backward(grad_out)
  File "/lib/python3.10/site-packages/torch/_tensor.py", line 531, in backward
    torch.autograd.backward(
  File "/lib/python3.10/site-packages/torch/autograd/__init__.py", line 289, in backward
    _engine_run_backward(
  File "/lib/python3.10/site-packages/torch/autograd/graph.py", line 768, in _engine_run_backward
    return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
  File "/lib/python3.10/site-packages/torch/_dynamo/compiled_autograd.py", line 292, in runtime_wrapper
    return compiled_fn(inputs, sizes, hooks)
  File "/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1556, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1565, in _call_impl
    return forward_call(*args, **kwargs)
  File "/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 433, in _fn
    return fn(*args, **kwargs)
  File "/lib/python3.10/site-packages/torch/fx/graph_module.py", line 738, in call_wrapped
    return self._wrapped_call(self, *args, **kwargs)
  File "/lib/python3.10/site-packages/torch/fx/graph_module.py", line 314, in __call__
    raise e.with_traceback(None)  # noqa: B904
```


### Versions

Collecting environment information...
PyTorch version: 2.4.0a0+git63a653e
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: 14.0.5 
CMake version: version 3.30.2
Libc version: glibc-2.35

Python version: 3.10.12 (main, Sep 11 2024, 15:47:36) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-5.15.0-113-generic-x86_64-with-glibc2.35
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Address sizes:                      43 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             12
On-line CPU(s) list:                0-11
Vendor ID:                          GenuineIntel
Model name:                         Intel(R) Xeon(R) Gold 5220R CPU @ 2.20GHz
CPU family:                         6
Model:                              85
Thread(s) per core:                 1
Core(s) per socket:                 6
Socket(s):                          2
Stepping:                           0
BogoMIPS:                           4389.68
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon nopl xtopology tsc_reliable nonstop_tsc cpuid tsc_known_freq pni pclmulqdq vmx ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single pti ssbd ibrs ibpb stibp tpr_shadow vnmi ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 invpcid avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xsaves arat pku ospke md_clear flush_l1d arch_capabilities
Virtualization:                     VT-x
Hypervisor vendor:                  VMware
Virtualization type:                full
L1d cache:                          384 KiB (12 instances)
L1i cache:                          384 KiB (12 instances)
L2 cache:                           12 MiB (12 instances)
L3 cache:                           71.5 MiB (2 instances)
NUMA node(s):                       1
NUMA node0 CPU(s):                  0-11
Vulnerability Gather data sampling: Unknown: Dependent on hypervisor status
Vulnerability Itlb multihit:        KVM: Mitigation: VMX disabled
Vulnerability L1tf:                 Mitigation; PTE Inversion; VMX flush not necessary, SMT disabled
Vulnerability Mds:                  Mitigation; Clear CPU buffers; SMT Host state unknown
Vulnerability Meltdown:             Mitigation; PTI
Vulnerability Mmio stale data:      Mitigation; Clear CPU buffers; SMT Host state unknown
Vulnerability Retbleed:             Mitigation; IBRS
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; IBRS; IBPB conditional; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Syscall hardening, KVM SW loop
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] torch==2.4.0a0+git63a653e
[pip3] torch_tb_profiler==0.4.0
[pip3] torchaudio==2.4.0a0+69d4077
[pip3] torchdata==0.7.1+5e6f7b7
[pip3] torchmetrics==1.4.1
[pip3] torchtext==0.18.0a0+9bed85d
[pip3] torchvision==0.19.0a0+48b1edf
[conda] Could not collect

cc @ezyang @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @amjames @rec @xmfan @yf225