Example #1
0
                        dest="costaugFlag",
                        default=True)
    parser.add_argument("--dynet-seed", type=int, dest="seed", default=0)
    parser.add_argument("--dynet-mem", type=int, dest="mem", default=0)

    args = parser.parse_args()

    #print 'Using external embedding:', args.external_embedding

    if args.predictFlag:
        with open(args.params, 'rb') as paramsfp:
            words, w2i, c2i, pos, rels, stored_opt = pickle.load(paramsfp)
        stored_opt.external_embedding = None
        print('Loading pre-trained model')
        parser = oldslavdep.OldSlavDep(words, pos, rels, w2i, c2i, stored_opt)
        parser.Load(args.model)

        testoutpath = os.path.join(args.output, args.conll_test_output)
        print('Predicting POS tags and parsing dependencies')
        # ts = time.time()
        # test_pred = list(parser.Predict(options.conll_test))
        # te = time.time()
        # print 'Finished in', te-ts, 'seconds.'
        # utils.write_conll(testoutpath, test_pred)

        with open(testoutpath, 'w') as fh:
            for sentence in parser.Predict(args.conll_test):
                for entry in sentence[1:]:
                    fh.write(str(entry) + '\n')
                fh.write('\n')
Example #2
0
        "pos_external_embedding"] == "None" else path_pos_embeddings  #os.sep.join([args.e,"UD_POS_embeddings",metadata[NAME_TREEBANK]])
    d["feats_external_embedding"] = None if d[
        "feats_external_embedding"] == "None" else path_feats_embeddings  #os.sep.join([args.e,"UD_FEATS_embeddings",metadata[NAME_TREEBANK]])
    d["lemmas_external_embedding"] = None

    print "pos_external_embeddings", d["pos_external_embedding"]
    print "feats_external_embeddings", d["feats_external_embedding"]
    print "external_embedding", d["external_embedding"]

    stored_opt = Namespace(**d)
    print "Running model with this configuration", stored_opt

    parser = lysfastparse.bcovington.covington.CovingtonBILSTM(
        words, lemmas, cpos, pos, feats, rels, w2i, l2i, stored_opt, None)

    parser.Load(path_model)

    with codecs.open(f_temp.name) as f_temp:

        lookup_conll_data = lysfastparse.utils.lookup_conll_extra_data(f_temp)

        testpath = f_temp.name
        ts = time.time()
        pred = list(parser.Predict(testpath))
        te = time.time()
        print "Took " + str(te - ts) + " seconds"
        lysfastparse.bcovington.utils_bcovington.write_conll(testpath, pred)

        lysfastparse.utils.dump_lookup_extra_into_conll(
            testpath, lookup_conll_data)
        lysfastparse.utils.transform_to_single_root(testpath)