code: def pick_layers_to_copy(n_student, n_teacher):
      try:
          val = LAYERS_TO_COPY[n_teacher][n_student]
          return val
      except KeyError:
          if n_student != n_teacher:
              warnings.warn(
                  f"no hardcoded layers to copy for teacher {n_teacher} -> student {n_student}, defaulting to first"
                  f" {n_student}"
              )
          return list(range(n_student))
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/seq2seq-distillation/make_student.py
imports: import warnings
  from pathlib import Path
  from typing import List, Tuple, Union
  import fire
  from torch import nn
  from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, PreTrainedModel
  from transformers.utils import logging
label_desc: Use image node_id 2 for calling a global function with example usage: pick_layers_to_copy(n_student, n_teacher) and returns: val, list