code: def show_results(
      x: LMTensorText, y, samples, outs, ctxs=None, max_n=10, **kwargs
  ):
      if ctxs is None:
          ctxs = get_empty_df(min(len(samples), max_n))
      for i, l in enumerate(["input", "target"]):
          ctxs = [
              b.show(ctx=c, label=l, **kwargs)
              for b, c, _ in zip(samples.itemgot(i), ctxs, range(max_n))
          ]
      ctxs = [
          b.show(ctx=c, label="pred", **kwargs)
          for b, c, _ in zip(outs.itemgot(0), ctxs, range(max_n))
      ]
      display_df(pd.DataFrame(ctxs))
      return ctxs
  
imports: from __future__ import annotations
  from ..basics import *
  from .core import *
  from .data import *
  from .models.core import *
  from .models.awdlstm import *
  from ..callback.rnn import *
  from ..callback.progress import *
  from .models.core import _model_meta
label_desc: Use image node_id 11 for calling a global function with example usage: show_results(x, y, samples, outs, ctxs, max_n) and returns: ctxs