torch_use_cuda_dsa to enable device-side assertions 1. 解释torch_use_cuda_dsa的含义 torch_use_cuda_dsa 是PyTorch 中的一个编译选项,用于启用设备端断言(Device-Side Assertions)。设备端断言是一种调试工具,可以在 CUDA 操作的运行时检查操作是否按预期执行。如果发现错误,它会立即停止操作并提供详细的错误...
192.168.37.6: For debugging consider passing CUDA_LAUNCH_BLOCKING=1. 192.168.37.6: Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions. export TORCH_USE_CUDA_DSA=1 以上train在V100-32GB*16,大概率显存不足。 发布于 2024-01-14 13:51・广东...
Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions. Traceback (most recent call last): File "/home/ma-user/work/pretrain/peft-baichuan2-13b-1/train.py", line 285, in <module> main() File "/home/ma-user/work/pretrain/peft-baichuan2-13b-1/train.py", line 268, ...
RuntimeError: CUDA error: out of memory; Compile with TORCH_USE_CUDA_DSA to enable device-side assertions For my case, I did upgrade NVIDIA drivers to 5.30 version from 5.25 that cause this problem. So, the solution is to downgrade my NVIDIA drivers back to 5.25 version and using the la...
RuntimeError: CUDA error: device-side assert triggered CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1. Compile with TORCH_USE_CUDA_DSA to enable device-side assertions. ...
[rank0]: return t.to( [rank0]: ^^^ [rank0]: RuntimeError: CUDA error: out of memory [rank0]: Compile withTORCH_USE_CUDA_DSAto enable device-side assertions.
CUDA error: initialization error CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1 Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions. ...
提示:Python 运行时抛出了一个异常。请检查疑难解答页面。CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.For debugging consider passing CUDA_LAUNCH_BLOCKING=1.Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions. ...
Compilewith`TORCH_USE_CUDA_DSA`toenable device-sideassertions. 参考地址:https://www.codetd.com/ru/article/14935168 默认使用0号GPU,但是0号GPU已经被占用了,所以要在代码中修改默认GPU编号,此修改要在import torch之前 importosos.environ["CUDA_VISIBLE_DEVICES"] ='1'...
Compile withTORCH_USE_CUDA_DSAto enable device-side assertions. 2024-03-29 18:28:51,875 xinference.api.restful_api 8 ERROR [address=0.0.0.0:43266, pid=897] CUDA error: invalid argument CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might...