code: def _one_emb_sz(classes, n, sz_dict=None):
      "Pick an embedding size for `n` depending on `classes` if not given in `sz_dict`."
      sz_dict = ifnone(sz_dict, {})
      n_cat = len(classes[n])
      sz = sz_dict.get(n, int(emb_sz_rule(n_cat)))  # rule of thumb
      return n_cat, sz
  
file_path: fastai/fastai/tabular/model.py
imports: from __future__ import annotations
  from ..torch_basics import *
  from .core import *
label_desc: Use image node_id 2 for calling a global function with example usage: _one_emb_sz(classes, n, sz_dict) and returns: n_cat,  sz