result.write(str(idx + 1) + '.\n')
result.write("GOLD\n" +
gold.encode('ascii', 'ignore').decode('utf-8', 'ignore') +
'\n')
result.write(
"GEN\n" +
beam.encode('ascii', 'ignore').decode('utf-8', 'ignore').lower() +
'\n\n')
return preds, golds
if __name__ == "__main__":
args = parse_args()
args.eval = True
dataset = PaperDataset(args)
args = set_args(args, dataset)
model = Model(args)
state_dict = torch.load(args.save,
map_location=lambda storage, location: storage)
model.load_state_dict(state_dict)
model = model.to(args.device)
model.args = args
model.maxlen = args.maxlen
model.starttok = dataset.OUTPUT.vocab.stoi['<start>']
model.endtok = dataset.OUTPUT.vocab.stoi['<eos>']
model.eostok = dataset.OUTPUT.vocab.stoi['.']
test(args, dataset, model)
# evaluate(model, dataset, args) # uncomment this and comment above in order to check loss and PPL
