4
0
mirror of https://github.com/nerfstudio-project/nerfstudio.git synced 2026-11-11 02:24:38 +08:00
nerfstudio/tests/data/test_datamanager.py
Jonáš Kulhánek 1147fe4d5c
Make VanillaDataManager generic (#1868)
* Make VanillaDataManager generic

* Remove removed classes from docs

* Simplify generic datamanager

* Simplify code

* Add serialization tests
2023-05-06 09:54:52 -07:00

108 lines
3.1 KiB
Python

# pylint: disable=all
from copy import copy
from typing import Any
import pytest
import torch
import yaml
from nerfstudio.cameras.cameras import Cameras
from nerfstudio.configs.base_config import InstantiateConfig
from nerfstudio.data.datamanagers.base_datamanager import (
DataManager,
DataparserOutputs,
VanillaDataManager,
VanillaDataManagerConfig,
)
from nerfstudio.data.datasets.base_dataset import InputDataset
from nerfstudio.data.datasets.depth_dataset import DepthDataset
class DummyDataParser:
def __init__(self, *args, **kwargs):
pass
def __getattr__(self, __name: str) -> Any:
if __name.startswith("_"):
return object.__getattribute__(self, __name)
return None
def get_dataparser_outputs(self, *args, **kwargs):
return DataparserOutputs(
[],
Cameras(
torch.ones((0, 3, 4)),
torch.ones((0, 1)),
torch.ones((0, 1)),
torch.ones((0, 1)),
torch.ones((0, 1)),
10,
10,
),
metadata={"depth_filenames": [], "depth_unit_scale_factor": 1.0},
)
@pytest.fixture
def config():
config = VanillaDataManagerConfig()
setattr(config, "dataparser", InstantiateConfig(_target=DummyDataParser))
setattr(config.dataparser, "data", None)
return config
def test_data_manager_type_inference(config):
# Mock for a faster test
assert VanillaDataManager(config).dataset_type is InputDataset
assert VanillaDataManager[DepthDataset](config).dataset_type is DepthDataset
class tmp(VanillaDataManager):
pass
assert tmp(config).dataset_type is InputDataset
class tmp2(VanillaDataManager[DepthDataset]):
pass
assert tmp2(config).dataset_type is DepthDataset
def test_data_manager_type_can_be_serialized(config):
# Mock for a faster test
assert VanillaDataManager(config).dataset_type is InputDataset
obj = yaml.load(yaml.dump(VanillaDataManager(config)), Loader=yaml.UnsafeLoader)
assert obj.dataset_type is InputDataset
assert isinstance(obj, VanillaDataManager)
assert VanillaDataManager[DepthDataset](config).dataset_type is DepthDataset
obj = yaml.load(yaml.dump(VanillaDataManager[DepthDataset](config)), Loader=yaml.UnsafeLoader)
assert obj.dataset_type is DepthDataset
assert isinstance(obj, VanillaDataManager)
class tmp(VanillaDataManager):
pass
try:
globals()["tmp"] = tmp
assert tmp(config).dataset_type is InputDataset
obj = yaml.load(yaml.dump(tmp(config)), Loader=yaml.UnsafeLoader)
assert obj.dataset_type is InputDataset
assert isinstance(obj, tmp)
finally:
globals().pop("tmp")
class tmp2(VanillaDataManager[DepthDataset]):
pass
try:
globals()["tmp2"] = tmp2
assert tmp2(config).dataset_type is DepthDataset
obj = yaml.load(yaml.dump(tmp2(config)), Loader=yaml.UnsafeLoader)
assert obj.dataset_type is DepthDataset
assert isinstance(obj, tmp2)
finally:
globals().pop("tmp2")