如果遇到"Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False"错误,我们使用map_location=torch.device('cpu')参数将模型参数保存在CPU上加载。 这个示例代码演示了一个实际应用场景,其中我们根据CUDA的可用性加载模型并正确处理"Attempting to deserialize object on a CUDA ...
遇到RuntimeError: attempting to deserialize object on CUDA device 0 but torch.cuda.is_available() is False 或类似的错误时,这通常意味着你尝试在一个不支持CUDA的设备上加载一个预期在CUDA上运行的PyTorch模型或张量。以下是一些解决这个问题的步骤和考虑点: 1. 确认错误信息完整性和上下文 首先,确保你看到...
当遇到"Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False"错误时,可以参考以下示例代码: pythonCopy codeimporttorch# 检查CUDA是否可用iftorch.cuda.is_available():device=torch.device("cuda")else:device=torch.device("cpu")# 加载模型并将其移动到正确的设备上mod...
报错信息:RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location='cpu' to map your storages to the CPU. 解决办法: 在GPU环境训练,在CPU环境部署: torch.load...
报错内容:RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU. ...
RuntimeError: Attempting to deserialize object on CUDA device 1 but torch.cuda.device_count() is 1. 问题:服务器上多块卡,使用其中一张训练的模型,在本地预测的时候报错。 解决:在torch.load中加入map_location,指定一块卡
raise RuntimeError('Attempting to deserialize object on a CUDA ' RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your sto...
RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU....
RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU. ...
错误信息: RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location='cpu' to map your storages to the CPU. ...