Skip to content

about transfer learning #420

@rookiecoder-chen

Description

@rookiecoder-chen

Is it right for me to do this? The code works, but I don't know if this is the right process...
# Set up the regressor.
device = chainer.get_device(args.device)
model_path = os.path.join(args.in_dir, args.model_filename)
metrics_fun = {'mae': F.mean_absolute_error, 'rmse': rmse}
regressor = Regressor.load_pickle('result/pretrain_qm9.pkl', device=device)
mlp = MLP(out_dim=class_num, hidden_dim=args.unit_num)
predictor = regressor.predictor
new_predictor = GraphConvPredictor(predictor, mlp=mlp)
new_regressor = Regressor(new_predictor,lossfun=F.mean_squared_error,
metrics_fun=metrics_fun, device=device)

print('Training...')
run_train(new_regressor, dataset, valid=None, batch_size=args.batchsize, epoch=args.epoch, out=args.out,
          device=device, converter=megnet_converter, resume_path=None,
          extensions_list=[extensions.PlotReport(['main/loss', 'validation/main/loss'], 'epoch',
                                                 filename='-trans-megnet-full-loss.svg', marker='None'),
                           extensions.PlotReport(['main/rmse', 'validation/main/rmse'], 'epoch',
                                                 filename='trans-megnet-full-rmse.svg', marker='None'),
                           extensions.PlotReport(['main/mae', 'validation/main/mae'], 'epoch',
                                                 filename='trans-megnet-full-mae.svg', marker='None')])

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Type

    No type

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions