code: def show_batch(
      x: TensorText,
      y,
      samples,
      ctxs=None,
      max_n=10,
      trunc_at=150,
      **kwargs,
  ):
      if ctxs is None:
          ctxs = get_empty_df(min(len(samples), max_n))
      if trunc_at is not None:
          samples = L(
              (s[0].truncate(trunc_at), *s[1:]) for s in samples
          )
      ctxs = show_batch[object](
          x, y, samples, max_n=max_n, ctxs=ctxs, **kwargs
      )
      display_df(pd.DataFrame(ctxs))
      return ctxs
  
imports: from __future__ import annotations
  from ..torch_basics import *
  from ..data.all import *
  from .core import *
label_desc: Use image node_id 6 for calling a global function with example usage: show_batch(x, y, samples, ctxs, max_n, trunc_at) and returns: ctxs