    def build_data_act_rec(self):
        """action recognition task, e.g., kinetics400"""
        templates = kinetics_templates if not self.is_ssv2 else ssv2_templates
        text = list(set([e["caption"] for e in self.raw_anno_list]))
        text2label = {e: i for i, e in enumerate(text)}
        text = [[t.format(e) for t in templates] for e in text]
        text = [e for l in text for e in l]
        self.text = [pre_text(e) for e in text]
        self.num_prompts = len(templates)
        self.img2txt = {i: text2label[e["caption"]] for i, e in enumerate(self.raw_anno_list)}
        self.txt2img = [[] for _ in range(len(text) // len(templates))]
        for i, e in enumerate(self.raw_anno_list):
            self.image.append(e["image"])
            self.txt2img[text2label[e["caption"]]].append(i)
        # logger.info(self.text)
        logger.info(f"Action recognition, number of prompts: {self.num_prompts}")
        logger.info(f"Action recognition, number of classes: {len(self.text)}")
action recognition task, e.g., kinetics400
videomamba/video_mm/dataset/caption_dataset.py