please use torch.load with map_location=torch.device(‘cpu’) to map your storages to the CPU.
问题描述：
在GPU环境下，用pytorch框架训练好的网络模型，在CPU环境测试，报错如下：
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.
可定位到报错行的代码是模型加载部分：
torch.load('xxxNet.pth')
其中，‘xxxNet.pth’ 是用GPU训练好的模型权重文件。
解决方案：
在模型加载时，指定 map_location='cpu' 即可，代码如下：
torch.load('xxxNet.pth', map_location='cpu')