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https://github.com/nerfstudio-project/nerfstudio.git
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d542646c72
* `isort` -> `ruff` * `pylint` -> `ruff` * Remove line * More minor cleanup * Better documentation for rules we are enabling * Fix gitignore, run black * vscode settings --------- Co-authored-by: Matt Tancik <mattt4001@gmail.com>
105 lines
3.0 KiB
Python
105 lines
3.0 KiB
Python
from typing import Any
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import pytest
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import torch
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import yaml
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from nerfstudio.cameras.cameras import Cameras
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from nerfstudio.configs.base_config import InstantiateConfig
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from nerfstudio.data.datamanagers.base_datamanager import (
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DataparserOutputs,
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VanillaDataManager,
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VanillaDataManagerConfig,
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)
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from nerfstudio.data.datasets.base_dataset import InputDataset
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from nerfstudio.data.datasets.depth_dataset import DepthDataset
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class DummyDataParser:
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def __init__(self, *args, **kwargs):
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pass
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def __getattr__(self, __name: str) -> Any:
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if __name.startswith("_"):
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return object.__getattribute__(self, __name)
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return None
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def get_dataparser_outputs(self, *args, **kwargs):
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return DataparserOutputs(
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[],
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Cameras(
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torch.ones((0, 3, 4)),
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torch.ones((0, 1)),
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torch.ones((0, 1)),
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torch.ones((0, 1)),
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torch.ones((0, 1)),
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10,
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10,
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),
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metadata={"depth_filenames": [], "depth_unit_scale_factor": 1.0},
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)
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@pytest.fixture
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def config():
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config = VanillaDataManagerConfig()
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setattr(config, "dataparser", InstantiateConfig(_target=DummyDataParser))
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setattr(config.dataparser, "data", None)
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return config
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def test_data_manager_type_inference(config):
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# Mock for a faster test
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assert VanillaDataManager(config).dataset_type is InputDataset
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assert VanillaDataManager[DepthDataset](config).dataset_type is DepthDataset
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class tmp(VanillaDataManager):
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pass
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assert tmp(config).dataset_type is InputDataset
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class tmp2(VanillaDataManager[DepthDataset]):
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pass
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assert tmp2(config).dataset_type is DepthDataset
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def test_data_manager_type_can_be_serialized(config):
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# Mock for a faster test
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assert VanillaDataManager(config).dataset_type is InputDataset
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obj = yaml.load(yaml.dump(VanillaDataManager(config)), Loader=yaml.UnsafeLoader)
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assert obj.dataset_type is InputDataset
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assert isinstance(obj, VanillaDataManager)
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assert VanillaDataManager[DepthDataset](config).dataset_type is DepthDataset
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obj = yaml.load(yaml.dump(VanillaDataManager[DepthDataset](config)), Loader=yaml.UnsafeLoader)
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assert obj.dataset_type is DepthDataset
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assert isinstance(obj, VanillaDataManager)
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class tmp(VanillaDataManager):
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pass
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try:
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globals()["tmp"] = tmp
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assert tmp(config).dataset_type is InputDataset
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obj = yaml.load(yaml.dump(tmp(config)), Loader=yaml.UnsafeLoader)
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assert obj.dataset_type is InputDataset
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assert isinstance(obj, tmp)
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finally:
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globals().pop("tmp")
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class tmp2(VanillaDataManager[DepthDataset]):
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pass
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try:
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globals()["tmp2"] = tmp2
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assert tmp2(config).dataset_type is DepthDataset
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obj = yaml.load(yaml.dump(tmp2(config)), Loader=yaml.UnsafeLoader)
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assert obj.dataset_type is DepthDataset
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assert isinstance(obj, tmp2)
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finally:
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globals().pop("tmp2")
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