988ee51b15466231e9770f46dcb4d221866322a7,OpenNMT/onmt/Translator.py,Translator,__init__,#Translator#,7

Before Change

        self.tt = torch.cuda if opt.cuda else torch

        checkpoint = torch.load(opt.model)
        self.model = checkpoint["model"]

        self.model.eval()

        if opt.cuda:
            self.model.cuda()
        else:
            self.model.cpu()

        self.src_dict = checkpoint["dicts"]["src"]

After Change

        decoder = onmt.Models.Decoder(model_opt, self.tgt_dict)
        model = onmt.Models.NMTModel(encoder, decoder)

        generator = nn.Sequential(
            nn.Linear(model_opt.rnn_size, self.tgt_dict.size()),
            nn.LogSoftmax())

        model.load_state_dict(checkpoint["model"])
        generator.load_state_dict(checkpoint["generator"])

Instances