How to use the fvcore.nn.weight_init.c2_msra_fill function in fvcore

groups=num_groups,
            dilation=dilation,
            norm=get_norm(norm, bottleneck_channels),
        )

        self.conv3 = Conv2d(
            bottleneck_channels,
            out_channels,
            kernel_size=1,
            bias=False,
            norm=get_norm(norm, out_channels),
        )

        for layer in [self.conv1, self.conv2, self.conv3, self.shortcut]:
            if layer is not None:  # shortcut can be None
                weight_init.c2_msra_fill(layer)

Args:
            norm (str or callable): a callable that takes the number of
                channels and return a `nn.Module`, or a pre-defined string
                (one of {"FrozenBN", "BN", "GN"}).
        """
        super().__init__()
        self.conv1 = Conv2d(
            in_channels,
            out_channels,
            kernel_size=7,
            stride=2,
            padding=3,
            bias=False,
            norm=get_norm(norm, out_channels),
        )
        weight_init.c2_msra_fill(self.conv1)