def __init__(
        self, input_shape: ShapeSpec, *, conv_dims: List[int], fc_dims: List[int], conv_norm=""
    ):
        """
        NOTE: this interface is experimental.

        Args:
            input_shape (ShapeSpec): shape of the input feature.
            conv_dims (list[int]): the output dimensions of the conv layers
            fc_dims (list[int]): the output dimensions of the fc layers
            conv_norm (str or callable): normalization for the conv layers.
                See :func:`detectron2.layers.get_norm` for supported types.
        """
        super().__init__()
        assert len(conv_dims) + len(fc_dims) > 0

        self._output_size = (input_shape.channels, input_shape.height, input_shape.width)

        self.conv_norm_relus = []
        for k, conv_dim in enumerate(conv_dims):
            conv = Conv2d(
                self._output_size[0],
                conv_dim,
                kernel_size=3,
                padding=1,
                bias=not conv_norm,
                norm=get_norm(conv_norm, conv_dim),
                activation=nn.ReLU(),
            )
            self.add_module("conv{}".format(k + 1), conv)
            self.conv_norm_relus.append(conv)
            self._output_size = (conv_dim, self._output_size[1], self._output_size[2])

        self.fcs = []
        for k, fc_dim in enumerate(fc_dims):
            if k == 0:
                self.add_module("flatten", nn.Flatten())
            fc = nn.Linear(int(np.prod(self._output_size)), fc_dim)
            self.add_module("fc{}".format(k + 1), fc)
            self.add_module("fc_relu{}".format(k + 1), nn.ReLU())
            self.fcs.append(fc)
            self._output_size = fc_dim

        for layer in self.conv_norm_relus:
            weight_init.c2_msra_fill(layer)
        for layer in self.fcs:
            weight_init.c2_xavier_fill(layer)

        NOTE: this interface is experimental.

        Args:
            input_shape (ShapeSpec): shape of the input feature.
            conv_dims (list[int]): the output dimensions of the conv layers
            fc_dims (list[int]): the output dimensions of the fc layers
            conv_norm (str or callable): normalization for the conv layers.
                See :func:`detectron2.layers.get_norm` for supported types.
        
video_chat_text/video_chat_with_MOSS/models/grit_src/third_party/CenterNet2/detectron2/modeling/roi_heads/box_head.py