tinywisdom opened a new issue, #18655:
URL: https://github.com/apache/tvm/issues/18655
### Summary
Creating a TVM `cuda` target and then importing an unrelated Python package
(`torchmetrics`) causes an immediate segmentation fault. There is no model
compilation or runtime execution involved—simply constructing a target triggers
the problem.
The crash occurs inside LLVM initialization, specifically in COFF directive
parser global constructors (e.g., `llvm::opt::OptTable::buildPrefixChars()` and
`_GLOBAL__sub_I_COFFDirectiveParser.cpp`), during dynamic library loading
(`dlopen`).
The behavior suggests a dynamic linking / multiple-LLVM interaction.
---
### Minimal Reproduction
```python
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import tvm
from tvm import target
from torchmetrics import Accuracy # segmentation fault occurs here in my
environment
def main():
print("Creating CUDA target...")
tgt = target.Target("cuda -arch=sm_86")
print("Target created:", tgt)
metric = Accuracy(task="multiclass", num_classes=10)
print("Metric created:", metric)
if __name__ == "__main__":
main()
```
### Actual Behavior
On my machine, the process prints "Creating CUDA target…" and then crashes
with segmentation fault during import of `torchmetrics`. The beginning of the
backtrace is:
```
!!!!!!! Segfault encountered !!!!!!!
File "<unknown>", in llvm::opt::OptTable::buildPrefixChars()
File "<unknown>", in COFFOptTable::COFFOptTable()
File "<unknown>", in _GLOBAL__sub_I_COFFDirectiveParser.cpp
File "./elf/dl-init.c", in call_init
File "./elf/dl-open.c", in dl_open_worker
...
Segmentation fault (core dumped)
```
Full trace is long but mostly `dlopen` / `dl-init` frames followed by LLVM
initialization frames.
---
### Expected Behavior
Importing `torchmetrics` after TVM target construction should not crash,
especially before any compilation or runtime invocation occurs. The two
libraries are unrelated and no model is passed to TVM.
---
### Notes on Repro Properties
* The issue does **not** require PyTorch, transformers, or CUDA execution.
* The critical step is:
```
tgt = target.Target("cuda -arch=sm_86")
```
followed by importing a package that triggers its own dynamic-library /
symbol loading chain.
* The failure happens even if `Accuracy` is never called.
* Removing the TVM target creation avoids the crash.
### Environment
```
OS: Linux x86_64 (glibc-based)
Python: 3.10.16 (conda-forge)
NumPy: 2.2.6
PyTorch: 2.9.0+cu128
Torchmetrics: <version depends on pip/conda> # fill here if needed
TVM: 0.22.0
LLVM: 17.0.6 (from tvm.support.libinfo())
GIT_COMMIT_HASH: 9dbf3f22ff6f44962472f9af310fda368ca85ef2
GPU: sm_86 (Ampere)
TVM target: cuda -keys=cuda,gpu -arch=sm_86 -max_num_threads=1024
-thread_warp_size=32
CUDA toolkit: likely 12.8 (based on PyTorch +cu128 build)
```
### Triage
Please refer to the list of label tags
[here](https://github.com/apache/tvm/wiki/Issue-Triage-Labels) to find the
relevant tags and add them below in a bullet format (example below).
* needs-triage
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