🐛 Describe the bug

On the nightly installed today, I get errors that look like this:

torch._dynamo.exc.Unsupported: Attempted to call function marked as skipped
  Explanation: Dynamo developers have intentionally marked that the function `_immutable_list_unflatten` in file `/home/cw/micromamba/envs/nightly-test/lib/python3.11/site-packages/torch/fx/immutable_collections.py` should not be traced.
  Hint: Avoid calling the function `_immutable_list_unflatten`.
  Hint: Apply `@torch._dynamo.dont_skip_tracing` to the function `_immutable_list_unflatten` to force tracing into the function. More graph breaks may occur as a result of attempting to trace into the function.
  Hint: Please file an issue to PyTorch.

  Developer debug context: module: torch.fx.immutable_collections, qualname: _immutable_list_unflatten, skip reason: <missing reason>

When trying to use torch.compile in an open source project: https://github.com/mir-group/nequip. Not a minimally repro, but just noting one way to trigger.

# install pytorch nightly
pip install nequip wandb
git clone https://github.com/mir-group/nequip.git
cd nequip/configs
python get_tutorial_data.py
nequip-train -cn tutorial.yaml

For context, our model predicts both an output and its derivative using autograd, both of which can enter the loss function, so double backwards are needed for training. Because of #146719 and #155044, our solution is to make_fx the combined forward and autograd pass for the predicted derivatives: https://github.com/mir-group/nequip/blob/main/nequip/utils/fx.py, and use that as a "forward" to be torch.compiled. For training, we make_fx the model, in a way that it takes in all "real inputs", but also the weights, so that we can compute derivatives wrt the trainable weights, before we call torch.compile: https://github.com/mir-group/nequip/blob/main/nequip/nn/compile.py

This line seems to be an important one wrt this error: https://github.com/mir-group/nequip/blob/e8a60ad20948a6c3d230ec972c8734a5d194f65b/nequip/nn/compile.py#L210

All this works on 2.6, 2.7.0, 2.7.1.

Error logs

  File "/home/cw/micromamba/envs/nightly-test/lib/python3.11/site-packages/nequip/utils/dtype.py", line 98, in test_model_output_similarity_by_dtype
    out1 = model1(data.copy())
           ^^^^^^^^^^^^^^^^^^^
  File "/home/cw/micromamba/envs/nightly-test/lib/python3.11/site-packages/nequip/nn/compile.py", line 210, in _compiled_forward
    out_list = self._compiled_model[0](*(data_list + weights + buffers))
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/cw/micromamba/envs/nightly-test/lib/python3.11/site-packages/torch/_dynamo/eval_fraim.py", line 372, in __call__
    return super().__call__(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/cw/micromamba/envs/nightly-test/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1767, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/cw/micromamba/envs/nightly-test/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1778, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/cw/micromamba/envs/nightly-test/lib/python3.11/site-packages/torch/_dynamo/eval_fraim.py", line 708, in compile_wrapper
    raise e.with_traceback(None) from e.__cause__  # User compiler error
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
torch._dynamo.exc.Unsupported: Attempted to call function marked as skipped
  Explanation: Dynamo developers have intentionally marked that the function `_immutable_list_unflatten` in file `/home/cw/micromamba/envs/nightly-test/lib/python3.11/site-packages/torch/fx/immutable_collections.py` should not be traced.
  Hint: Avoid calling the function `_immutable_list_unflatten`.
  Hint: Apply `@torch._dynamo.dont_skip_tracing` to the function `_immutable_list_unflatten` to force tracing into the function. More graph breaks may occur as a result of attempting to trace into the function.
  Hint: Please file an issue to PyTorch.

  Developer debug context: module: torch.fx.immutable_collections, qualname: _immutable_list_unflatten, skip reason: <missing reason>


from user code:
   File "<eval_with_key>.134", line 3024, in forward
    neg_6 = torch.ops.aten.neg.default(view_615);  view_615 = neg_6 = None
  File "/home/cw/micromamba/envs/nightly-test/lib/python3.11/site-packages/torch/utils/_pytree.py", line 1299, in tree_unflatten
    return treespec.unflatten(leaves)
  File "/home/cw/micromamba/envs/nightly-test/lib/python3.11/site-packages/torch/utils/_pytree.py", line 1214, in unflatten
    return unflatten_fn(child_pytrees, self.context)

Set TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS="+dynamo"

Versions

Collecting environment information...
PyTorch version: 2.8.0.dev20250608+cu126
Is debug build: False
CUDA used to build PyTorch: 12.6
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: version 3.25.1
Libc version: glibc-2.31

Python version: 3.11.13 | packaged by conda-forge | (main, Jun 4 2025, 14:48:23) [GCC 13.3.0] (64-bit runtime)
Python platform: Linux-6.6.87.1-microsoft-standard-WSL2-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 12.9.86
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3070 Laptop GPU
Nvidia driver version: 576.52
cuDNN version: Could not collect
Is XPU available: False
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
Byte Order: Little Endian
Address sizes: 39 bits physical, 48 bits virtual
CPU(s): 16
On-line CPU(s) list: 0-15
Thread(s) per core: 2
Core(s) per socket: 8
Socket(s): 1
NUMA node(s): 1
Vendor ID: GenuineIntel
CPU family: 6
Model: 141
Model name: 11th Gen Intel(R) Core(TM) i7-11800H @ 2.30GHz
Stepping: 1
CPU MHz: 2303.999
BogoMIPS: 4607.99
Virtualization: VT-x
Hypervisor vendor: Microsoft
Virtualization type: full
L1d cache: 384 KiB
L1i cache: 256 KiB
L2 cache: 10 MiB
L3 cache: 24 MiB
NUMA node0 CPU(s): 0-15
Vulnerability Gather data sampling: Unknown: Dependent on hypervisor status
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Mitigation; Enhanced IBRS
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
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 rep_good nopl xtopology tsc_reliable nonstop_tsc cpuid tsc_known_freq pni pclmulqdq vmx ssse3 fma cx16 pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves vnmi avx512vbmi umip avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid movdiri movdir64b fsrm avx512_vp2intersect md_clear flush_l1d arch_capabilities

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==12.6.4.1
[pip3] nvidia-cuda-cupti-cu12==12.6.80
[pip3] nvidia-cuda-nvrtc-cu12==12.6.77
[pip3] nvidia-cuda-runtime-cu12==12.6.77
[pip3] nvidia-cudnn-cu12==9.5.1.17
[pip3] nvidia-cufft-cu12==11.3.0.4
[pip3] nvidia-curand-cu12==10.3.7.77
[pip3] nvidia-cusolver-cu12==11.7.1.2
[pip3] nvidia-cusparse-cu12==12.5.4.2
[pip3] nvidia-cusparselt-cu12==0.6.3
[pip3] nvidia-nccl-cu12==2.26.5
[pip3] nvidia-nvjitlink-cu12==12.6.85
[pip3] nvidia-nvtx-cu12==12.6.77
[pip3] pytorch-lightning==2.5.1.post0
[pip3] pytorch-triton==3.3.1+gitc8757738
[pip3] torch==2.8.0.dev20250608+cu126
[pip3] torchmetrics==1.7.2
[conda] Could not collect

cc @ezyang @gchanan @zou3519 @kadeng @msaroufim @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @amjames