def main():
args = parse_args()
OpenKSModel.list_modules()
model: ExpertRecModel = OpenKSModel.get_module("PyTorch", "HGTExpertRec")(
"openks/data/nsf_dblp_kg/nsfkg/", args)
model.preprocess_data()
model.load_data_and_model()
logger.info('Training HGT with #param: %d' % model.get_n_params())
model.train_expert()
model.evaluate()
# Copyright (c) 2022 OpenKS Authors, SCIR, HIT.
# All Rights Reserved.
from openks.models import OpenKSModel
import argparse
# 列出已加载模型
OpenKSModel.list_modules()
parser = argparse.ArgumentParser(
description=
'Implement of SISO, SIMO, MISO, MIMO for Conditional Statement Extraction')
# Model parameters.
parser.add_argument('--train',
type=str,
default='data/stmts-train.tsv',
help='location of the labeled training set')
parser.add_argument('--eval',
type=str,
default='data/stmts-eval.tsv',
help='location of the evaluation set')
parser.add_argument('--model_name',
type=str,
default='MIMO_BERT_LSTM',
help='the model to be trained')
parser.add_argument('--language_model',
type=str,
default='resources/model.pt',
help='language model checkpoint to use')
parser.add_argument('--wordembed',
type=str,