Files
EasyFace/tests/trainers/test_plug_finetune_text_generation.py
2023-03-02 11:17:26 +08:00

52 lines
1.7 KiB
Python

# Copyright (c) Alibaba, Inc. and its affiliates.
import argparse
import os
import shutil
import tempfile
import unittest
from modelscope.hub.snapshot_download import snapshot_download
from modelscope.metainfo import Trainers
from modelscope.msdatasets import MsDataset
from modelscope.trainers import build_trainer
from modelscope.utils.constant import ModelFile
from modelscope.utils.test_utils import test_level
def test_trainer_with_model_and_args():
def concat_answer_context(dataset):
dataset['src_txt'] = dataset['answers']['text'][0] + '[SEP]' + dataset[
'context']
return dataset
from datasets import load_dataset
dataset_dict = load_dataset('luozhouyang/dureader', 'robust')
train_dataset = dataset_dict['train'].map(concat_answer_context) \
.rename_columns({'question': 'tgt_txt'}).remove_columns('context') \
.remove_columns('id').remove_columns('answers')
eval_dataset = dataset_dict['validation'].map(concat_answer_context) \
.rename_columns({'question': 'tgt_txt'}).remove_columns('context') \
.remove_columns('id').remove_columns('answers')
tmp_dir = tempfile.TemporaryDirectory().name
if not os.path.exists(tmp_dir):
os.makedirs(tmp_dir)
model_id = 'damo/nlp_plug_text-generation_27B'
kwargs = dict(model=model_id,
train_dataset=train_dataset,
eval_dataset=eval_dataset,
work_dir=tmp_dir)
trainer = build_trainer(name=Trainers.nlp_plug_trainer,
default_args=kwargs)
trainer.train()
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--local_rank')
test_trainer_with_model_and_args()