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Fixed transforms that did not work with new versions of PyTorch. #139

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Fixed transforms that did not work with new versions of PyTorch. #139

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11 changes: 6 additions & 5 deletions engine/data/transforms/_transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,8 +54,9 @@ class PadToSize(T.Pad):
Mask,
BoundingBoxes,
)
def _get_params(self, flat_inputs: List[Any]) -> Dict[str, Any]:
sp = F.get_spatial_size(flat_inputs[0])
def make_params(self, flat_inputs: List[Any]) -> Dict[str, Any]:
get_size_func = F.get_size if hasattr(F, "get_size") else F.get_spatial_size
sp = get_size_func(flat_inputs[0])
h, w = self.size[1] - sp[0], self.size[0] - sp[1]
self.padding = [0, 0, w, h]
return dict(padding=self.padding)
Expand All @@ -66,7 +67,7 @@ def __init__(self, size, fill=0, padding_mode='constant') -> None:
self.size = size
super().__init__(0, fill, padding_mode)

def _transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
def transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
fill = self._fill[type(inpt)]
padding = params['padding']
return F.pad(inpt, padding=padding, fill=fill, padding_mode=self.padding_mode) # type: ignore[arg-type]
Expand Down Expand Up @@ -101,7 +102,7 @@ def __init__(self, fmt='', normalize=False) -> None:
self.fmt = fmt
self.normalize = normalize

def _transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
def transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
spatial_size = getattr(inpt, _boxes_keys[1])
if self.fmt:
in_fmt = inpt.format.value.lower()
Expand All @@ -124,7 +125,7 @@ def __init__(self, dtype='float32', scale=True) -> None:
self.dtype = dtype
self.scale = scale

def _transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
def transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
inpt = F.pil_to_tensor(inpt)
if self.dtype == 'float32':
inpt = inpt.float()
Expand Down