Method forward

models/point_encoder.py:193–224

(self, pts, colors)

    def forward(self, pts, colors):
        # divide the point cloud in the same form. This is important
        _, center, features = self.group_divider(pts, colors)

        # encoder the input cloud patches
        group_input_tokens = self.encoder(features)  #  B G N
        group_input_tokens = self.encoder2trans(group_input_tokens)
        # prepare cls
        cls_tokens = self.cls_token.expand(group_input_tokens.size(0), -1, -1)  
        cls_pos = self.cls_pos.expand(group_input_tokens.size(0), -1, -1)  
        # add pos embedding
        pos = self.pos_embed(center)
        # final input
        x = torch.cat((cls_tokens, group_input_tokens), dim=1)
        pos = torch.cat((cls_pos, pos), dim=1)
        # transformer
        x = x + pos
        # x = x.half()
        
        # a patch_dropout of 0. would mean it is disabled and this function would do nothing but return what was passed in
        x = self.patch_dropout(x)

        x = self.visual.pos_drop(x)

        # ModuleList not support forward
        for i, blk in enumerate(self.visual.blocks):
            x = blk(x)
        x = self.visual.norm(x[:, 0, :])
        x = self.visual.fc_norm(x)

        x = self.trans2embed(x)
        return x