def __init__(self, in_features, n_bins=16, mlp_dim=256, min_depth=1e-3, max_depth=10):
        """Bin center regressor network. Bin centers are unbounded

        Args:
            in_features (int): input channels
            n_bins (int, optional): Number of bin centers. Defaults to 16.
            mlp_dim (int, optional): Hidden dimension. Defaults to 256.
            min_depth (float, optional): Not used. (for compatibility with SeedBinRegressor)
            max_depth (float, optional): Not used. (for compatibility with SeedBinRegressor)
        """
        super().__init__()
        self.version = "1_1"
        self._net = nn.Sequential(
            nn.Conv2d(in_features, mlp_dim, 1, 1, 0),
            nn.ReLU(inplace=True),
            nn.Conv2d(mlp_dim, n_bins, 1, 1, 0),
            nn.Softplus()
        )
Bin center regressor network. Bin centers are unbounded

        Args:
            in_features (int): input channels
            n_bins (int, optional): Number of bin centers. Defaults to 16.
            mlp_dim (int, optional): Hidden dimension. Defaults to 256.
            min_depth (float, optional): Not used. (for compatibility with SeedBinRegressor)
            max_depth (float, optional): Not used. (for compatibility with SeedBinRegressor)
        
ControlNet-v1-1-nightly/annotator/zoe/zoedepth/models/layers/localbins_layers.py