def __init__(self, cfg: CfgNode, input_channels: int):
        """
        Initialize DensePose fully convolutional head

        Args:
            cfg (CfgNode): configuration options
            input_channels (int): number of input channels
        """
        super(DensePoseV1ConvXHead, self).__init__()
        # fmt: off
        hidden_dim           = cfg.MODEL.ROI_DENSEPOSE_HEAD.CONV_HEAD_DIM
        kernel_size          = cfg.MODEL.ROI_DENSEPOSE_HEAD.CONV_HEAD_KERNEL
        self.n_stacked_convs = cfg.MODEL.ROI_DENSEPOSE_HEAD.NUM_STACKED_CONVS
        # fmt: on
        pad_size = kernel_size // 2
        n_channels = input_channels
        for i in range(self.n_stacked_convs):
            layer = Conv2d(n_channels, hidden_dim, kernel_size, stride=1, padding=pad_size)
            layer_name = self._get_layer_name(i)
            self.add_module(layer_name, layer)
            n_channels = hidden_dim
        self.n_out_channels = n_channels
        initialize_module_params(self)

        Initialize DensePose fully convolutional head

        Args:
            cfg (CfgNode): configuration options
            input_channels (int): number of input channels
        
EVA-02/det/projects/DensePose/densepose/modeling/roi_heads/v1convx.py