def forward(self, imgs, txt_ids):
        """
        imgs:       [B, 3, H, W] of torch.float32.
        - mean:     [0.48145466, 0.4578275, 0.40821073]
        - std:      [0.26862954, 0.26130258, 0.27577711]
        txt_ids:    [B, L] of torch.long.
                    Encoded by data.CLIPTokenizer.
        """
        xi = self.visual(imgs)
        xt = self.textual(txt_ids)
        return xi, xt

        imgs:       [B, 3, H, W] of torch.float32.
        - mean:     [0.48145466, 0.4578275, 0.40821073]
        - std:      [0.26862954, 0.26130258, 0.27577711]
        txt_ids:    [B, L] of torch.long.
                    Encoded by data.CLIPTokenizer.
        
diffsynth/models/wan_video_image_encoder.py