(
self,
keys: KeysCollection,
range_x: tuple[float, float] | float = 0.0,
range_y: tuple[float, float] | float = 0.0,
range_z: tuple[float, float] | float = 0.0,
prob: float = 0.1,
keep_size: bool = True,
mode: SequenceStr = GridSampleMode.BILINEAR,
padding_mode: SequenceStr = GridSamplePadMode.BORDER,
align_corners: Sequence[bool] | bool = False,
dtype: Sequence[DtypeLike | torch.dtype] | DtypeLike | torch.dtype = np.float32,
allow_missing_keys: bool = False,
lazy: bool = False,
)
| 1855 | backend = RandRotate.backend |
| 1856 | |
| 1857 | def __init__( |
| 1858 | self, |
| 1859 | keys: KeysCollection, |
| 1860 | range_x: tuple[float, float] | float = 0.0, |
| 1861 | range_y: tuple[float, float] | float = 0.0, |
| 1862 | range_z: tuple[float, float] | float = 0.0, |
| 1863 | prob: float = 0.1, |
| 1864 | keep_size: bool = True, |
| 1865 | mode: SequenceStr = GridSampleMode.BILINEAR, |
| 1866 | padding_mode: SequenceStr = GridSamplePadMode.BORDER, |
| 1867 | align_corners: Sequence[bool] | bool = False, |
| 1868 | dtype: Sequence[DtypeLike | torch.dtype] | DtypeLike | torch.dtype = np.float32, |
| 1869 | allow_missing_keys: bool = False, |
| 1870 | lazy: bool = False, |
| 1871 | ) -> None: |
| 1872 | MapTransform.__init__(self, keys, allow_missing_keys) |
| 1873 | RandomizableTransform.__init__(self, prob) |
| 1874 | LazyTransform.__init__(self, lazy=lazy) |
| 1875 | self.rand_rotate = RandRotate( |
| 1876 | range_x=range_x, range_y=range_y, range_z=range_z, prob=1.0, keep_size=keep_size, lazy=lazy |
| 1877 | ) |
| 1878 | self.mode = ensure_tuple_rep(mode, len(self.keys)) |
| 1879 | self.padding_mode = ensure_tuple_rep(padding_mode, len(self.keys)) |
| 1880 | self.align_corners = ensure_tuple_rep(align_corners, len(self.keys)) |
| 1881 | self.dtype = ensure_tuple_rep(dtype, len(self.keys)) |
| 1882 | |
| 1883 | @LazyTransform.lazy.setter # type: ignore |
| 1884 | def lazy(self, val: bool): |
nothing calls this directly
no test coverage detected