pytorch - 💡(How to fix) Fix torch.compile Inductor crashes on InstanceNorm2d + RReLU + flatten + BatchNorm1d

🐛 Describe the bug

torch.compile with the Inductor backend crashes on a pure PyTorch model containing InstanceNorm2d, RReLU, flatten, exp(clamp(...)), and BatchNorm1d.

Eager execution runs successfully, but torch.compile raises an InductorError with an internal assertion failure:

AssertionError: unexpected group: ((8, 7, 9), ()) != (56, 9), ()

import torch
import torch.nn as nn

torch.manual_seed(31)

in2d = nn.InstanceNorm2d(7)
rrelu = nn.RReLU().eval()
bn1 = nn.BatchNorm1d(63).eval()
x = torch.randn([8, 7, 3, 3])

def model():
    t = in2d(x)
    t = rrelu(t)
    t = torch.flatten(t, start_dim=1)
    t = torch.exp(torch.clamp(t, max=10))
    return bn1(t)

model()

torch._dynamo.reset()

try:
    torch.compile(model, backend="inductor")()
    print("OK")
except Exception as e:
    msg = str(e).splitlines()[0]
    matched = "unexpected group" in str(e) or "AssertionError" in str(e)
    print(f"raised: {type(e).__name__}: {msg[:120]}")
    print("BUG" if matched else "?")

Error logs

raised: InductorError: AssertionError: unexpected group: ((8, 7, 9), ()) != (56, 9), ()
BUG

Versions

PyTorch version: 2.11.0+cu130 Is debug build: False CUDA used to build PyTorch: 13.0 ROCM used to build PyTorch: N/A

OS: Ubuntu 24.04.2 LTS (x86_64) GCC version: (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0 Clang version: Could not collect CMake version: Could not collect Libc version: glibc-2.39

Python version: 3.10.20 (main, Mar 11 2026, 17:46:40) [GCC 14.3.0] (64-bit runtime) Python platform: Linux-5.15.167.4-microsoft-standard-WSL2-x86_64-with-glibc2.39 Is CUDA available: False CUDA runtime version: Could not collect CUDA_MODULE_LOADING set to: N/A GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3080 Laptop GPU Nvidia driver version: 545.92 cuDNN version: Could not collect Is XPU available: False HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True Caching allocator config: N/A

Versions of relevant libraries: [pip3] numpy==2.2.6 [pip3] onnx==1.21.0 [pip3] onnx2torch==1.5.15 [pip3] onnxruntime==1.23.2 [pip3] torch==2.11.0 [pip3] torchvision==0.26.0 [pip3] triton==3.6.0

cc @chauhang @penguinwu @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @kadeng @muchulee8 @amjames @aakhundov @coconutruben @jataylo