尽管torch.compile在自动生成CUDA优化内核方面表现出色,但在实际应用中,仍然可能会遇到一些挑战。比如,对于一些复杂的模型结构和动态计算图,torch.compile可能会遇到编译失败或性能提升不明显的问题。这时候,就需要开发者深入了解torch.compile的工作原理,通过调整编译参数、优化模型代码等方式来解决问题。 在面对编译失
尽管torch.compile在自动生成CUDA优化内核方面表现出色,但在实际应用中,仍然可能会遇到一些挑战。比如,对于一些复杂的模型结构和动态计算图,torch.compile可能会遇到编译失败或性能提升不明显的问题。这时候,就需要开发者深入了解torch.compile的工作原理,通过调整编译参数、优化模型代码等方式来解决问题。 在面对编译失败时,...
这通常涉及到设置适当的编译选项,如 USE_CUDA=1。 重新编译时,还可以启用 TORCH_USE_CUDA_DSA 以启用设备端断言,这有助于在设备端捕获错误。编译命令可能类似于: bash export MAX_JOBS=8 python setup.py bdist_wheel 在编译之前,请确保你的开发环境中安装了所有必要的依赖项,并且你的CUDA安装是完整和正确...
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...
For debugging consider passing CUDA_LAUNCH_BLOCKING=1. 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/pre...
🐛 Describe the bug When trying to compile a simple function that uses cpu tensors, torch inductor initialises a context on cuda:0. If used in a multiprocessing context (E.G.) a torch dataloader, this quickly results in OOM (simple repro ...
nitialization error CUDA kernel errors CUDA_LAUNCH_BLOCKING=1 Compile with `TORCH_USE_CUDA_DSA`,x传入的不是list,而是tensor。原因是pytorch。改成list就没有这个问题。
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...
I instantiate model, then wrap it with FSDP, and then do model = model.compile(). Both fp16 and bf16 produces NaNs (which is really weird). Using different lengths in CrossAttention with torch.compile throws any of "Triton Error [CUDA]: unspecified launch failure", "CUDA error: an ...