code: def test_generate_merged_ids_returns_tensor(
      tokenizer, input_ids, target_ids
  ):
      # Test that the function returns torch.Tensor objects
      merged_ids, attention_masks = generate_merged_ids(
          input_ids, target_ids, tokenizer
      )
      assert isinstance(merged_ids, torch.Tensor)
      assert isinstance(attention_masks, torch.Tensor)
  
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 14 for calling a global function with example usage: test_generate_merged_ids_returns_tensor(tokenizer, input_ids, target_ids) without return types