def init_weights(self) -> None:
        """Initialize position embedding and mask token of MAE decoder."""
        super().init_weights()

        if self.reconstruction_type == 'pixel':
            decoder_pos_embed = build_2d_sincos_position_embedding(
                int(self.num_patches**.5),
                self.decoder_pos_embed.shape[-1],
                cls_token=False)
            self.decoder_pos_embed.data.copy_(decoder_pos_embed.float())

            torch.nn.init.normal_(self.mask_token, std=.02)
        else:
            self.rescale_init_weight()
Initialize position embedding and mask token of MAE decoder.
mmpretrain/models/necks/itpn_neck.py