def __init__(self, in_features: int, lateral_features: int):
        """
        A Feature Pyramid Network Layer (FPN) layer. It creates a feature map by aggregating features from the previous
        and backbone layer. Due to the spatial mismatch, the tensor coming from the previous layer is upsampled.

        Args:
            in_features (`int`):
                The number of input features (channels).
            lateral_features (`int`):
                The number of lateral features (channels).
        """
        super().__init__()
        self.proj = nn.Sequential(
            nn.Conv2d(lateral_features, in_features, kernel_size=1, padding=0, bias=False),
            nn.GroupNorm(32, in_features),
        )

        self.block = MaskFormerFPNConvLayer(in_features, in_features)

        A Feature Pyramid Network Layer (FPN) layer. It creates a feature map by aggregating features from the previous
        and backbone layer. Due to the spatial mismatch, the tensor coming from the previous layer is upsampled.

        Args:
            in_features (`int`):
                The number of input features (channels).
            lateral_features (`int`):
                The number of lateral features (channels).
        
dpkd/transformers/src/transformers/models/maskformer/modeling_maskformer.py