def test_persist_1(data):
class _Trainer(BaseRunner):
def __init__(self):
super().__init__()
self.model = SequentialLinear(50, 2)
def predict(self, x_, y_): # noqa
return x_, y_
p = Persist()
with pytest.raises(ValueError,
match='can not access property `path` before training'):
p.path
p.before_proc(trainer=_Trainer())
assert p.path == str(Path('.').resolve() / Path(os.getcwd()).name)
with pytest.raises(ValueError,
match='can not reset property `path` after training'):
p.path = 'aa'
p = Persist('test_model')
p.before_proc(trainer=_Trainer())
assert p.path == str(Path('.').resolve() / 'test_model')
assert (Path('.').resolve() / 'test_model' / 'describe.pkl.z').exists()
assert (Path('.').resolve() / 'test_model' / 'init_state.pth.s').exists()
assert (Path('.').resolve() / 'test_model' / 'model.pth.m').exists()
assert (Path('.').resolve() / 'test_model' /
'model_structure.pkl.z').exists()
p = Persist('test_model', increment=True)
p.before_proc(trainer=_Trainer())
assert p.path == str(Path('.').resolve() / 'test_model@1')
def test_persist_save_checkpoints(data):
class _Trainer(BaseRunner):
def __init__(self):
super().__init__()
self.model = SequentialLinear(50, 2)
def predict(self, x_, y_): # noqa
return x_, y_
cp_1 = Trainer.checkpoint_tuple(
id='cp_1',
iterations=111,
model_state=SequentialLinear(50, 2).state_dict(),
)
cp_2 = Trainer.checkpoint_tuple(
id='cp_2',
iterations=111,
model_state=SequentialLinear(50, 2).state_dict(),
)
# save checkpoint
p = Persist('test_model_1', increment=False, only_best_states=False)
p.before_proc(trainer=_Trainer())
p.on_checkpoint(cp_1)
p.on_checkpoint(cp_2)
assert (Path('.').resolve() / 'test_model_1' / 'checkpoints' /
'cp_1.pth.s').exists()
assert (Path('.').resolve() / 'test_model_1' / 'checkpoints' /
'cp_2.pth.s').exists()
# reduced save checkpoint
p = Persist('test_model_2', increment=False, only_best_states=True)
p.before_proc(trainer=_Trainer())
p.on_checkpoint(cp_1)
p.on_checkpoint(cp_2)
assert (Path('.').resolve() / 'test_model_2' / 'checkpoints' /
'cp.pth.s').exists()
assert not (Path('.').resolve() / 'test_model_2' / 'checkpoints' /
'cp_1.pth.s').exists()
assert not (Path('.').resolve() / 'test_model_2' / 'checkpoints' /
'cp_2.pth.s').exists()
# no checkpoint will be saved
p = Persist('test_model_3', increment=False, only_best_states=True)
p.before_proc(trainer=_Trainer())
p.on_checkpoint(cp_2)
assert not (Path('.').resolve() / 'test_model_3' / 'checkpoints' /
'cp.pth.s').exists()
assert not (Path('.').resolve() / 'test_model_3' / 'checkpoints' /
'cp_2.pth.s').exists()