code: def _get_iw_info(
      learn, ds_idx: int = 0  # Index in `learn.dls`
  ) -> list:
      "For every image in `dls` `zip` it's `Path`, target and loss"
      dl = learn.dls[ds_idx].new(shuffle=False, drop_last=False)
      probs, targs, preds, losses = learn.get_preds(
          dl=dl, with_input=False, with_loss=True, with_decoded=True
      )
      targs = [dl.vocab[t] for t in targs]
      return L([dl.dataset.items, targs, losses]).zip()
  
imports: from __future__ import annotations
  from ..torch_basics import *
  from ..data.all import *
  from .core import *
  from fastcore.parallel import *
  from ipywidgets import HBox, VBox, widgets, Button, Checkbox, Dropdown, Layout, Box, Output, Label, FileUpload
label_desc: Use image node_id 6 for calling a global function with example usage: _get_iw_info(learn, ds_idx) and returns: L