1.torch.jit.save
torch.jit.save用来保存编译后的模型，支持跨平台，要注意模型中只能使用pytorch的函数。
jit.save支持保存script类型和trace类型的模型，其中script为全量模型，trace为仅保存运行过的路径
2.torch.save
torch.save有三种使用场景，参考：https://stackoverflow.com/questions/42703500/best-way-to-save-a-trained-model-in-pytorch
1.保存模型用来做测试
torch.save(model.state_dict(), filepath) #Later to restore: model.load_state_dict(torch.load(filepath)) model.eval()
2.用来恢复训练状态
state = {
'epoch': epoch,
'state_dict': model.state_dict(),
'optimizer': optimizer.state_dict(),
...
}
torch.save(state, filepath)
#later
model.load_state_dict(state['state_dict'])
optimizer.load_state_dict(state['optimizer'])
Since you are resuming training, DO NOT call model.eval() once you restore the states when loading.
3.用来给不不知道你的网络结构的人使用
torch.save(model, filepath) # Then later: model = torch.load(filepath)
This way is still not bullet proof and since pytorch is still undergoing a lot of changes, I wouldn’t recommend it.
