mat1 and mat2 must have the same dtype, but got BFloat16 and Float

[hjj-lmx]

# 初始化推理状态
    inference_state = sam2_model.video_predictor.init_state(video_path=input_video_path)

    # 传入的是多帧的mask数组
    for mask_object in mask_objects:
        mask_byte = down_file.url_to_byte(mask_object.get("mask_url"))
        image_data = io.BytesIO(mask_byte)
        mask_image = Image.open(image_data).convert('L')  # 转换为灰度图
        transform = transforms.Compose([
            transforms.ToTensor(),
            transforms.Lambda(lambda x: (x > 0.5).float())
        ])
        mask = transform(mask_image)
        mask = mask.squeeze(0)
        sam2_model.video_predictor.add_new_mask(inference_state,
                                                mask_object.get("frame_idx"),
                                                mask_object.get("frame_idx"),
                                                mask)
    # 传播提示获取整个视频的masklet
    video_segments = {}
    for out_frame_idx, out_obj_ids, out_mask_logits in sam2_model.video_predictor.propagate_in_video(
            inference_state):
        video_segments[out_frame_idx] = {
            out_obj_id: (out_mask_logits[i] > 0.0).cpu().numpy()
            for i, out_obj_id in enumerate(out_obj_ids)
        }

mask_objects的长度是1的适合能正常运行，大于1就报错