code: def test_extract_tensors():
      # Create a sample model
      model = SampleModel()
  
      # Call extract_tensors function
      stripped_model, tensors = extract_tensors(model)
  
      # Assert that the model and tensors are returned
      assert isinstance(stripped_model, torch.nn.Module)
      assert isinstance(tensors, list)
  
      # Assert that the tensors contain the expected keys
      for tensor_dict in tensors:
          assert "params" in tensor_dict
          assert "buffers" in tensor_dict
  
      # Assert that all model parameters are set to None
      for module in stripped_model.modules():
          for name, param in module.named_parameters(recurse=False):
              assert param is None
  
          for name, buf in module.named_buffers(recurse=False):
              assert buf is None
  
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 1 for calling a global function with example usage: test_extract_tensors() without return types