解决torch.load将模型引入cpu问题。

>>> torch.load('tensors.pt') # Load all tensors onto the CPU >>> torch.load('tensors.pt', map_location=torch.device('cpu')) # Load all tensors onto the CPU, using a function >>> torch.load('tensors.pt', map_location=lambda storage, loc: storage) # Load all tensors onto GPU 1 >>> torch.load('tensors.pt', map_location=lambda storage, loc: storage.cuda(1)) # Map tensors from GPU 1 to GPU 0 >>> torch.load('tensors.pt', map_location={'cuda:1':'cuda:0'}) # Load tensor from io.BytesIO object >>> with open('tensor.pt', 'rb') as f: ... buffer = io.BytesIO(f.read()) >>> torch.load(buffer) # Load a module with 'ascii' encoding for unpickling >>> torch.load('module.pt', encoding='ascii')