def __init__(self, features, activation, bn):
        """Init.

        Args:
            features (int): number of features
        """
        super().__init__()

        self.bn = bn

        self.groups=1

        self.conv1 = nn.Conv2d(features, features, kernel_size=3, stride=1, padding=1, bias=True, groups=self.groups)
        
        self.conv2 = nn.Conv2d(features, features, kernel_size=3, stride=1, padding=1, bias=True, groups=self.groups)

        if self.bn == True:
            self.bn1 = nn.BatchNorm2d(features)
            self.bn2 = nn.BatchNorm2d(features)

        self.activation = activation

        self.skip_add = nn.quantized.FloatFunctional()
Init.

        Args:
            features (int): number of features
        
depth_anything_v2/util/blocks.py