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

74 lines
3.0 KiB
Python

# Copyright (c) Alibaba, Inc. and its affiliates.
import os
import shutil
import tempfile
import unittest
from modelscope.hub.snapshot_download import snapshot_download
from modelscope.models.cv.video_summarization import PGLVideoSummarization
from modelscope.msdatasets.task_datasets import VideoSummarizationDataset
from modelscope.trainers import build_trainer
from modelscope.utils.config import Config
from modelscope.utils.constant import ModelFile
from modelscope.utils.logger import get_logger
from modelscope.utils.test_utils import test_level
logger = get_logger()
class VideoSummarizationTrainerTest(unittest.TestCase):
def setUp(self):
print(('Testing %s.%s' % (type(self).__name__, self._testMethodName)))
self.tmp_dir = tempfile.TemporaryDirectory().name
if not os.path.exists(self.tmp_dir):
os.makedirs(self.tmp_dir)
self.model_id = 'damo/cv_googlenet_pgl-video-summarization'
self.cache_path = snapshot_download(self.model_id)
self.config = Config.from_file(
os.path.join(self.cache_path, ModelFile.CONFIGURATION))
self.dataset_train = VideoSummarizationDataset('train',
self.config.dataset,
self.cache_path)
self.dataset_val = VideoSummarizationDataset('test',
self.config.dataset,
self.cache_path)
def tearDown(self):
shutil.rmtree(self.tmp_dir, ignore_errors=True)
super().tearDown()
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
def test_trainer(self):
kwargs = dict(model=self.model_id,
train_dataset=self.dataset_train,
eval_dataset=self.dataset_val,
work_dir=self.tmp_dir)
trainer = build_trainer(default_args=kwargs)
trainer.train()
results_files = os.listdir(self.tmp_dir)
self.assertIn(f'{trainer.timestamp}.log.json', results_files)
for i in range(2):
self.assertIn(f'epoch_{i+1}.pth', results_files)
@unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
def test_trainer_with_model_and_args(self):
model = PGLVideoSummarization.from_pretrained(self.cache_path)
kwargs = dict(cfg_file=os.path.join(self.cache_path,
ModelFile.CONFIGURATION),
model=model,
train_dataset=self.dataset_train,
eval_dataset=self.dataset_val,
max_epochs=2,
work_dir=self.tmp_dir)
trainer = build_trainer(default_args=kwargs)
trainer.train()
results_files = os.listdir(self.tmp_dir)
self.assertIn(f'{trainer.timestamp}.log.json', results_files)
for i in range(2):
self.assertIn(f'epoch_{i+1}.pth', results_files)
if __name__ == '__main__':
unittest.main()