RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:1 and cuda:0!
nuaabuaa07 opened this issue · comments
步骤3：合并ChatLaw权重并推理 ，这一步骤在执行时，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 index in method wrapper_CUDA__index_select) 。是不支持在多卡的机器上创建推理吗？
难道，推理服务，只能部署在单GPU的机器上？
单卡时报内存不足。
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 50.00 MiB (GPU 0; 22.20 GiB total capacity; 21.53 GiB already allocated; 48.12 MiB free; 21.55 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
我也遇到了相同的问题，但是我是单卡机器也是报错
RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!
请问有解决方案或者排查思路吗？
我也遇到了相同的问题，但是我是单卡机器也是报错 RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! 请问有解决方案或者排查思路吗？
找到解决方法了，因为transforms版本过高导致的报错，回退到4.29.0之后，问题解决
我也遇到了相同的问题，但是我是单卡机器也是报错 RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! 请问有解决方案或者排查思路吗？
找到解决方法了，因为transforms版本过高导致的报错，回退到4.29.0之后，问题解决
没找到这个版本啊，请问你是怎么安装的？
`
(base) ➜ pip install transforms==4.29.0
ERROR: Could not find a version that satisfies the requirement transforms==4.29.0 (from versions: 0.1, 0.2.0, 0.2.1)
ERROR: No matching distribution found for transforms==4.29.0
`
我也遇到了相同的问题，但是我是单卡机器也是报错 RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! 请问有解决方案或者排查思路吗？
找到解决方法了，因为transforms版本过高导致的报错，回退到4.29.0之后，问题解决
没找到这个版本啊，请问你是怎么安装的？ ` (base) ➜ pip install transforms==4.29.0 ERROR: Could not find a version that satisfies the requirement transforms==4.29.0 (from versions: 0.1, 0.2.0, 0.2.1) ERROR: No matching distribution found for transforms==4.29.0
`
不好意思，上面单词拼写有误，应该是transformers，请参考https://pypi.org/project/transformers/#history