def __init__(self, mean, std, inplace=False):
        """Normalize a tensor image with mean and standard deviation.
        .. note::
            This transform acts out of place by default, i.e., it does not mutates the input tensor.
        See :class:`~torchvision.transforms.Normalize` for more details.
        Args:
            tensor (Tensor): Tensor image of size (C, H, W) to be normalized.
            mean (sequence): Sequence of means for each channel.
            std (sequence): Sequence of standard deviations for each channel.
            inplace(bool,optional): Bool to make this operation inplace.
        Returns:
            Tensor: Normalized Tensor image.
        """

        self.mean = mean
        self.std = std
        self.inplace = inplace
Normalize a tensor image with mean and standard deviation.
        .. note::
            This transform acts out of place by default, i.e., it does not mutates the input tensor.
        See :class:`~torchvision.transforms.Normalize` for more details.
        Args:
            tensor (Tensor): Tensor image of size (C, H, W) to be normalized.
            mean (sequence): Sequence of means for each channel.
            std (sequence): Sequence of standard deviations for each channel.
            inplace(bool,optional): Bool to make this operation inplace.
        Returns:
            Tensor: Normalized Tensor image.
        
third-party/lama/models/ade20k/base.py