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utils: remove inplace opt-in from normalize

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Cédric Deltheil 2023-09-18 17:55:55 +02:00 committed by Cédric Deltheil
parent bce3910383
commit e319f13d05
1 changed files with 5 additions and 8 deletions
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13
src/refiners/fluxion/utils.py
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@ -37,21 +37,18 @@ def interpolate(x: Tensor, factor: float | torch.Size, mode: str = "nearest") ->
# Adapted from https://github.com/pytorch/vision/blob/main/torchvision/transforms/_functional_tensor.py # Adapted from https://github.com/pytorch/vision/blob/main/torchvision/transforms/_functional_tensor.py
def normalize( def normalize(
tensor: Float[Tensor, "*batch channels height width"], mean: list[float], std: list[float], inplace: bool = False tensor: Float[Tensor, "*batch channels height width"], mean: list[float], std: list[float]
) -> Float[Tensor, "*batch channels height width"]: ) -> Float[Tensor, "*batch channels height width"]:
assert tensor.is_floating_point() assert tensor.is_floating_point()
assert tensor.ndim >= 3 assert tensor.ndim >= 3
if not inplace:
tensor = tensor.clone()
dtype = tensor.dtype dtype = tensor.dtype
mean_tensor = torch.tensor(mean, dtype=dtype, device=tensor.device).view(-1, 1, 1) pixel_mean = torch.tensor(mean, dtype=dtype, device=tensor.device).view(-1, 1, 1)
std_tensor = torch.tensor(std, dtype=dtype, device=tensor.device).view(-1, 1, 1) pixel_std = torch.tensor(std, dtype=dtype, device=tensor.device).view(-1, 1, 1)
if (std_tensor == 0).any(): if (pixel_std == 0).any():
raise ValueError(f"std evaluated to zero after conversion to {dtype}, leading to division by zero.") raise ValueError(f"std evaluated to zero after conversion to {dtype}, leading to division by zero.")
return tensor.sub_(mean_tensor).div_(std_tensor) return (tensor - pixel_mean) / pixel_std
def image_to_tensor(image: Image.Image, device: Device | str | None = None, dtype: DType | None = None) -> Tensor: def image_to_tensor(image: Image.Image, device: Device | str | None = None, dtype: DType | None = None) -> Tensor: