how to save model for test?

[w5688414]

I want to save the trained model, and load it for prediction, here is my code:
`
saver = ModelSaver("./cache/model_ckpt_100.pkl")

model=ModelLoader.load_pytorch_model("./cache/model_ckpt_100.pkl")

ModelLoader.load_pytorch(model,"./cache/model_ckpt_100.pkl")
tester = Tester(datasets['test'], model, metrics=AccuracyMetric())
tester.test()
`
but it doesn't work, Can the author provide a way for prediction after saving the model

[LeeSureman]

Could you please show the error trace information?

[w5688414]

I change the code like this, and it works, thanks for your response, sorry to interrupt you
`
if(args.train):
trainer.train()
saver = ModelSaver("./cache/model_ckpt_100.pkl")
saver.save_pytorch(model,param_only=False)

if(args.predict):
model=ModelLoader.load_pytorch_model("./cache/model_ckpt_100.pkl")
# ModelLoader.load_pytorch(model,"./cache/model_ckpt_100.pkl")
# tester = Tester(datasets['test'], model, metrics=AccuracyMetric())
# tester.test()

from fastNLP import Tester

tester = Tester(datasets['test'], model, batch_size=args.test_batch, metrics=metrics)
tester.test()

`

[LeeSureman]

congratulations! And if you use fitlog, you can run 'fitlog log logs' in the project dictionary to scan the experiment result.

[zhangtianlin]

Dear w5688414 or LeeSureman:
i used the code
if(args.train):
trainer.train()
saver = ModelSaver("./cache/model_ckpt_100.pkl")
saver.save_pytorch(model,param_only=False)

if(args.predict):
model=ModelLoader.load_pytorch_model("./cache/model_ckpt_100.pkl")
tester = Tester(datasets['test'], model, batch_size=args.test_batch, metrics=metrics)
tester.test()

But it has error, which said TypeError: The type of model must be 'torch.nn.Module', got '<class'collections.OrderedDict'>'
i donot the reason. Who can help me?