def test_get_path(self):
class p:
_path: str
m_cfg = p()
m_cfg._path = 'm'
d_cfg = p()
d_cfg._path = 'd'
d_cfg.index_cross = 1
r_cfg = p()
r_cfg._path = 'r'
self.assertEqual(
get_path(m_cfg, d_cfg, r_cfg),
os.path.join(env.getdir(env.paths.save_folder), 'm-r-d-1'))
def setUpClass(cls):
cls.path = os.path.join(
env.getdir(env.paths.test_folder),
os.path.splitext(os.path.basename(__file__))[0], cls.__name__)
if not os.path.exists(cls.path):
os.makedirs(cls.path)
cls.old_save_folder = env.paths.save_folder
env.paths.save_folder = os.path.join(env.paths.test_folder, cls.path)
class SimpleModel(BaseModel):
def __init__(self, cfg, data_cfg, run, **kwargs):
super().__init__(cfg, data_cfg, run, **kwargs)
self.fc = nn.Linear(6, 3).to(self.device)
def train(self, epoch_info, sample_dict):
input = sample_dict['input'].to(self.device)
target = sample_dict['target'].to(self.device)
output = self.fc(input)
loss = F.l1_loss(output, target)
return {'loss': loss}
def test(self, batch_idx, sample_dict):
input = sample_dict['input'].to(self.device)
output = self.fc(input)
return {'output': output}
model_path = os.path.join(cls.path, 'model_configs.json')
with open(model_path, 'w') as f:
f.write(json.dumps(dict(name='SimpleModel')))
dataset_path = os.path.join(cls.path, 'dataset_configs.json')
with open(dataset_path, 'w') as f:
f.write(json.dumps(dict(index_cross=1)))
run_path = os.path.join(cls.path, 'run_configs.json')
with open(run_path, 'w') as f:
f.write(json.dumps(dict()))
cls.model = SimpleModel(BaseConfig(model_path),
BaseConfig(dataset_path), Run(run_path))
def setUpClass(cls):
cls.path = os.path.join(
env.getdir(env.paths.test_folder),
os.path.splitext(os.path.basename(__file__))[0], cls.__name__)
if not os.path.exists(cls.path):
os.makedirs(cls.path)
def test_getdir(self):
self.assertTrue(
os.path.samefile(env.getdir(env.paths.test_folder),
os.path.split(__file__)[0]))