Device map cuda. I can successfully specify 1 GPU using Oct 23, 2024 · 和之前...

Device map cuda. I can successfully specify 1 GPU using Oct 23, 2024 · 和之前的一些issue一样，使用V100 32G单卡推理时某些case会OOM，所以开了device_map希望把模型切分到多张卡上，但是用python和torchrun启动都会报错Expected all tensors to be on the same device, but found at least two devices, cuda:1 and cuda:0!，debug看了一下，具体问题出现在qwen2vl forward时 Dec 25, 2023 · Many thanks. no_grad contexts. is_available () is False. 0 Python 3. device context manager. Tensorのデバイス（GPU / CPU）を切り替えるには、to ()またはcuda (), cpu ()メソッドを使う。torch. create_voice_clone_prompt ( ref_audio= (ref_wavs [0], sr), # or "voice_design_reference. This is especially emphasised by the linked youtube May 24, 2024 · 为什么手工写的device_map会报错？ 如果报错 RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:1 and cuda:0! (when checking argument for argument mat2 in method wrapper_mm) Sep 3, 2023 · With older version, I achieved this nicely with the setup of CUDA_VISIBLE_DEVICES=6,7. I want to learn a bit more about how to design device maps but it seems like the documentation doesn’t have it (I tried following the hyperlink from “Handling Big Jul 10, 2023 · I was reading the tutorial for how to load large models for inference with accelerate (Handling big models for inference) and saw the note that device_map='auto' is not suitable for training because there are parts of the code wrapped in torch. Whether you’re just getting started or optimizing complex GPU kernels, this guide is an essential reference for effectively leveraging Dec 20, 2023 · Is there best practice to do this without the need of design a manual device_map? For example in process on a cluster with 4 gpus, I want to load model1 on gpu_ids=0,1,2 and model2 on gpu_ids=3 Mar 6, 2026 · CUDA Driver API (PDF) - v13. yupupr yatjbt xgubeq sdxyuf revoo jnysmp uhjah fccm nva nmhag