code: def test_find_embedding_layer_with_path_complex():
      # Test case 2: Test the function with a more complex module structure including AutoModelForCausalLM
      model = AutoModelForCausalLM.from_pretrained(
          "HuggingFaceM4/tiny-random-LlamaForCausalLM"
      )
  
      embedding_layer, path = find_embedding_layer_with_path(model)
      assert embedding_layer is not None
      assert isinstance(embedding_layer, torch.nn.Embedding)
      assert path == "model.embed_tokens"
  
imports: import pytest
  import torch
  from transformers import AutoModelForCausalLM
  from ludwig.utils.model_utils import contains_nan_or_inf_tensors, extract_tensors, find_embedding_layer_with_path, replace_tensors
label_desc: Use image node_id 4 for calling a global function with example usage: test_find_embedding_layer_with_path_complex() without return types