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from pytorch_caney.config import get_config
import argparse
import unittest
class TestConfig(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.config_yaml_path = 'pytorch_caney/' + \
'tests/config/test_config.yaml'
def test_default_config(self):
# Get the default configuration
args = argparse.Namespace(cfg=self.config_yaml_path)
config = get_config(args)
# Test specific configuration values
self.assertEqual(config.DATA.BATCH_SIZE, 128)
self.assertEqual(config.DATA.DATASET, 'MODIS')
self.assertEqual(config.MODEL.TYPE, 'swinv2')
self.assertEqual(config.MODEL.NAME, 'test_config')
self.assertEqual(config.TRAIN.EPOCHS, 800)
def test_custom_config(self):
# Test with custom arguments
args = argparse.Namespace(
cfg=self.config_yaml_path,
batch_size=64,
dataset='CustomDataset',
data_paths=['solongandthanksforallthefish'],
)
config = get_config(args)
# Test specific configuration values with custom arguments
self.assertEqual(config.DATA.BATCH_SIZE, 64)
self.assertEqual(config.DATA.DATASET, 'CustomDataset')
self.assertEqual(config.DATA.DATA_PATHS,
['solongandthanksforallthefish'])
if __name__ == '__main__':
unittest.main()
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