(
self,
keys: KeysCollection,
prob: float = 0.1,
min_zoom: Sequence[float] | float = 0.9,
max_zoom: Sequence[float] | float = 1.1,
mode: SequenceStr = InterpolateMode.AREA,
padding_mode: SequenceStr = NumpyPadMode.EDGE,
align_corners: Sequence[bool | None] | bool | None = None,
dtype: Sequence[DtypeLike | torch.dtype] | DtypeLike | torch.dtype = np.float32,
keep_size: bool = True,
allow_missing_keys: bool = False,
lazy: bool = False,
**kwargs,
)
| 2083 | backend = RandZoom.backend |
| 2084 | |
| 2085 | def __init__( |
| 2086 | self, |
| 2087 | keys: KeysCollection, |
| 2088 | prob: float = 0.1, |
| 2089 | min_zoom: Sequence[float] | float = 0.9, |
| 2090 | max_zoom: Sequence[float] | float = 1.1, |
| 2091 | mode: SequenceStr = InterpolateMode.AREA, |
| 2092 | padding_mode: SequenceStr = NumpyPadMode.EDGE, |
| 2093 | align_corners: Sequence[bool | None] | bool | None = None, |
| 2094 | dtype: Sequence[DtypeLike | torch.dtype] | DtypeLike | torch.dtype = np.float32, |
| 2095 | keep_size: bool = True, |
| 2096 | allow_missing_keys: bool = False, |
| 2097 | lazy: bool = False, |
| 2098 | **kwargs, |
| 2099 | ) -> None: |
| 2100 | MapTransform.__init__(self, keys, allow_missing_keys) |
| 2101 | RandomizableTransform.__init__(self, prob) |
| 2102 | LazyTransform.__init__(self, lazy=lazy) |
| 2103 | self.rand_zoom = RandZoom( |
| 2104 | prob=1.0, min_zoom=min_zoom, max_zoom=max_zoom, keep_size=keep_size, lazy=lazy, **kwargs |
| 2105 | ) |
| 2106 | self.mode = ensure_tuple_rep(mode, len(self.keys)) |
| 2107 | self.padding_mode = ensure_tuple_rep(padding_mode, len(self.keys)) |
| 2108 | self.align_corners = ensure_tuple_rep(align_corners, len(self.keys)) |
| 2109 | self.dtype = ensure_tuple_rep(dtype, len(self.keys)) |
| 2110 | |
| 2111 | @LazyTransform.lazy.setter # type: ignore |
| 2112 | def lazy(self, val: bool): |
nothing calls this directly
no test coverage detected