Is it possible to save a config dict along with the model parameters?

1

I am doing:

            torch.save(reconstruct_model.state_dict(), path.join(wandb.run.dir, 'best-model.pt'))

which saves my model parameters. Separately, I’m doing:

    open(path.join(wandb.run.dir, 'args.json'), 'w').write(json.dumps(vars(args)))

I’m wondering if I can just save those args in the best-model.pt file? Subsequently, when I load, currently, I do:

    spec = importlib.util.spec_from_file_location(
        "ReconstructionModel", saved_reconstruction_model_filepath)
    model_spec = importlib.util.module_from_spec(spec)
    spec.loader.exec_module(model_spec)

    model = model_spec.ReconstructionModel(kernel_size=masked_args['kernel_size'], kernel_size_step=masked_args['kernel_size_step'])

    state_dict = torch.load(model_path, map_location=device)

    model.load_state_dict(state_dict)

where the masked_args are read from the args.json file.

2

You can save objects in general.
You just need to create a dict with the parameters together with you dictionary.
Like

torch.save({'model':model.state_dict(),'my_params':...}
3

What about reading the params?

4

you just need to read it as if it were a dictionary.
Your params will be in torch.load(path)[‘my_params’]
and the model in model.load_state_dict(tocrch.load(path)[‘model’])