code: def __call__(self, sample, **kwargs):
      clip_meta = sample["clip_meta"].cpu()
      assert torch.all(torch.le(clip_meta[:, 4], clip_meta[:, 5]))
      text_meta = [tuple(item.tolist()) for item in clip_meta[:, 3:]]
  
      if hasattr(self, "retriver"):
          # build_retriver is called.
          self.retriver.add(
              sample["pooled_text"].cpu().numpy().astype("float32"),
              text_meta,
          )
      else:
          raise NotImplementedError
  
imports: import torch
  import os
  import numpy
  import pickle
  from .None import retri
  from ..utils import get_local_rank
label_desc: Use image node_id 2 for calling the TextClipVectorPool obj's underlying member method code with example usage: obj.__call__(sample) without return types