🐛 Describe the bug
Here is one case failed on riscv64 now:
More log is here:
inductor/test_extension_backend.py::ExtensionBackendTests::test_open_device_registration PASSED [4.8757s] [ 22%]
inductor/test_foreach.py::ForeachTests::test_cpu_cpp_fallback_foreach_map_clamp_max PASSED [4.9508s] [ 22%]
inductor/test_foreach.py::ForeachTests::test_cpu_cpp_fallback_foreach_map_clamp_min FAILED [10.2039s] [100%]
No verbose info here.
Versions
Collecting environment information...
PyTorch version: 2.13.0a0+git1449fa4
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A
OS: Debian GNU/Linux 13 (trixie) (riscv64)
GCC version: (Debian 14.2.0-19) 14.2.0
Clang version: 19.1.7 (3+b1)
CMake version: version 3.31.6
Libc version: glibc-2.41
Python version: 3.13.5 (main, Jun 25 2025, 18:55:22) [GCC 14.2.0] (64-bit runtime)
Python platform: Linux-6.6.0-138.0.0.121.oe2403sp3.riscv64-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
CPU:
Architecture: riscv64
Byte Order: Little Endian
CPU(s): 64
On-line CPU(s) list: 0-63
Vendor ID: 0x5b7
Model name: thead,c920
CPU family: 0x0
Model: 0x0
Thread(s) per core: 1
Core(s) per socket: 64
Socket(s): 1
L1d cache: 4 MiB (64 instances)
L1i cache: 4 MiB (64 instances)
L2 cache: 16 MiB (16 instances)
L3 cache: 64 MiB (1 instance)
NUMA node(s): 4
NUMA node0 CPU(s): 0-7,16-23
NUMA node1 CPU(s): 8-15,24-31
NUMA node2 CPU(s): 32-39,48-55
NUMA node3 CPU(s): 40-47,56-63
Versions of relevant libraries:
[pip3] mypy==1.16.0
[pip3] mypy_extensions==1.1.0
[pip3] numpy==2.1.2
[pip3] onnx==1.21.0
[pip3] onnx-ir==0.1.16
[pip3] onnxscript==0.6.2
[pip3] optree==0.13.0
[pip3] torch==2.13.0a0+git1449fa4
[conda] Could not collect
🐛 Describe the bug
Here is one case failed on riscv64 now:
More log is here:
No verbose info here.
Versions
Collecting environment information...
PyTorch version: 2.13.0a0+git1449fa4
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A
OS: Debian GNU/Linux 13 (trixie) (riscv64)
GCC version: (Debian 14.2.0-19) 14.2.0
Clang version: 19.1.7 (3+b1)
CMake version: version 3.31.6
Libc version: glibc-2.41
Python version: 3.13.5 (main, Jun 25 2025, 18:55:22) [GCC 14.2.0] (64-bit runtime)
Python platform: Linux-6.6.0-138.0.0.121.oe2403sp3.riscv64-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
CPU:
Architecture: riscv64
Byte Order: Little Endian
CPU(s): 64
On-line CPU(s) list: 0-63
Vendor ID: 0x5b7
Model name: thead,c920
CPU family: 0x0
Model: 0x0
Thread(s) per core: 1
Core(s) per socket: 64
Socket(s): 1
L1d cache: 4 MiB (64 instances)
L1i cache: 4 MiB (64 instances)
L2 cache: 16 MiB (16 instances)
L3 cache: 64 MiB (1 instance)
NUMA node(s): 4
NUMA node0 CPU(s): 0-7,16-23
NUMA node1 CPU(s): 8-15,24-31
NUMA node2 CPU(s): 32-39,48-55
NUMA node3 CPU(s): 40-47,56-63
Versions of relevant libraries:
[pip3] mypy==1.16.0
[pip3] mypy_extensions==1.1.0
[pip3] numpy==2.1.2
[pip3] onnx==1.21.0
[pip3] onnx-ir==0.1.16
[pip3] onnxscript==0.6.2
[pip3] optree==0.13.0
[pip3] torch==2.13.0a0+git1449fa4
[conda] Could not collect