code: def get_some_linear_layer(model):
      if model.config.model_type == "gpt2":
          return model.transformer.h[0].mlp.c_fc
      elif model.config.model_type == "opt":
          try:
              return model.decoder.layers[0].fc1
          except AttributeError:
              # for AutoModelforCausalLM
              return model.model.decoder.layers[0].fc1
      else:
          return model.transformer.h[0].mlp.dense_4h_to_h
  
imports: import gc
  import importlib.metadata
  import tempfile
  import unittest
  from packaging import version
  from transformers import AutoConfig, AutoModel, AutoModelForCausalLM, AutoModelForSeq2SeqLM, AutoModelForSequenceClassification, AutoTokenizer, BitsAndBytesConfig, pipeline
  from transformers.testing_utils import is_bitsandbytes_available, is_torch_available, require_accelerate, require_bitsandbytes, require_torch, require_torch_gpu, require_torch_multi_gpu, slow, torch_device
label_desc: Use image node_id 1 for calling a global function with example usage: get_some_linear_layer(model) and returns: model, model, model, model