def __init__(self, in_features: int, lateral_widths: List[int], feature_size: int = 256):
        """
        Feature Pyramid Network, given an input tensor and a set of feature map of different feature/spatial size, it
        creates a list of feature maps with the same feature size.

        Args:
            in_features (`int`):
                The number of input features (channels).
            lateral_widths (`List[int]`):
                A list with the features (channels) size of each lateral connection.
            feature_size (int, *optional*, defaults to 256):
                The features (channels) of the resulting feature maps.
        """
        super().__init__()
        self.stem = MaskFormerFPNConvLayer(in_features, feature_size)
        self.layers = nn.Sequential(
            *[MaskFormerFPNLayer(feature_size, lateral_width) for lateral_width in lateral_widths[::-1]]
        )

        Feature Pyramid Network, given an input tensor and a set of feature map of different feature/spatial size, it
        creates a list of feature maps with the same feature size.

        Args:
            in_features (`int`):
                The number of input features (channels).
            lateral_widths (`List[int]`):
                A list with the features (channels) size of each lateral connection.
            feature_size (int, *optional*, defaults to 256):
                The features (channels) of the resulting feature maps.
        
dpkd/transformers/src/transformers/models/maskformer/modeling_maskformer.py