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Unblock the process to upstream, so add it temporarily.
And it is okay to run with the same CI job. Cannot reproduce it on v100 manually also.
Versions
================ collect_env.py ================
Collecting environment information...
PyTorch version: 2.15.0a0+gited5a91a
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A
Python version: 3.13.5 (main, Jun 13 2026, 14:18:01) [GCC 14.2.0] (64-bit runtime)
Python platform: Linux-7.0.0-29-generic-riscv64-with-glibc2.41
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
Is XPU available: False
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: False
Caching allocator config: N/A
Activity
yuzibo commentedon Aug 26, 2026
This issue is reproducible on v100 and k1
add the test set to blocklist temporary
[native-dsl] Use `has_torch_function` in place of `check_has_torch_fu…