class_docstr: Interpretation base class, can be inherited for task specific Interpretation classes
docstr: Return inputs, preds, targs, decoded outputs, and losses at `idxs`
docstr_tok: ["Return","inputs",",","preds",",","targs",",","decoded","outputs",",","and","losses","at","`","idxs","`"]
code: def __getitem__(self, idxs):
      "Return inputs, preds, targs, decoded outputs, and losses at `idxs`"
      if isinstance(idxs, Tensor):
          idxs = idxs.tolist()
      if not is_listy(idxs):
          idxs = [idxs]
      items = getattr(self.dl.items, "iloc", L(self.dl.items))[idxs]
      tmp_dl = self.learn.dls.test_dl(
          items,
          with_labels=True,
          process=not isinstance(self.dl, TabDataLoader),
      )
      inps, preds, targs, decoded = self.learn.get_preds(
          dl=tmp_dl,
          with_input=True,
          with_loss=False,
          with_decoded=True,
          act=self.act,
          reorder=False,
      )
      return inps, preds, targs, decoded, self.losses[idxs]
  
imports: from __future__ import annotations
  from .data.all import *
  from .optimizer import *
  from .learner import *
  from .tabular.core import *
  import sklearn.metrics
label_desc: Use image node_id 2 for calling the Interpretation obj's underlying member method code with example usage: obj.__getitem__(idxs) and returns: inps,  preds,  targs,  decoded,  self