code: def test_neftune_hook_with_noise_alpha_train_mode():
      """Test that the NEFTuneHook is only applied when the module is in training mode."""
      (
          module_without_hook,
          module_with_hook,
      ) = _setup_models_for_neftune()
      _forward_pass_and_assert_neftune_hook(
          module_without_hook, module_with_hook, mode="train"
      )
  
imports: import pytest
  import torch
  from transformers import AutoConfig, AutoModelForCausalLM
  from ludwig.constants import LOGITS, PREDICTIONS, PROBABILITIES
  from ludwig.modules.training_hooks import NEFTuneHook
  from ludwig.utils.llm_utils import add_left_padding, create_attention_mask, FALLBACK_CONTEXT_LEN, find_last_matching_index, generate_merged_ids, get_context_len, get_realigned_target_and_prediction_tensors_for_inference, has_padding_token, pad_target_tensor_for_fine_tuning, remove_left_padding
  from ludwig.utils.tokenizers import HFTokenizer
label_desc: Use image node_id 19 for calling a global function with example usage: test_neftune_hook_with_noise_alpha_train_mode() without return types