code: def test_warn_completion_is_not_empty():
      df_all_empty = pd.DataFrame(
          {"prompt": ["prompt"] * 2, "completion": [""] * 2}
      )
  
      msg_all_empty = "TODO: Note all completion fields are empty. This is possibly expected for inference but not for training"
  
      assert warn_completion_is_not_empty(df_all_empty) == msg_all_empty
  
      df_some_empty = pd.DataFrame(
          {"prompt": ["prompt"] * 2, "completion": ["", "completion"]}
      )
  
      msg_some_empty = f"""TODO: completion contains {1} empty values at rows ({[0]})
                  Please check the original file that the fields for prompt template are 
                  not empty and rerun dataset validation"""
  
      assert (
          warn_completion_is_not_empty(df_some_empty) == msg_some_empty
      )
  
      df_no_empty = pd.DataFrame(
          {"prompt": ["prompt"] * 2, "completion": ["completion"] * 2}
      )
  
      assert warn_completion_is_not_empty(df_no_empty) is None
  
imports: import pandas
  import pytest
  from ..customization_dataset_preparation import convert_into_prompt_completion_only, convert_into_template, drop_duplicated_rows, drop_unrequired_fields, get_common_suffix, get_prepared_filename, parse_template, recommend_hyperparameters, show_first_example_in_df, split_into_train_validation, template_mapper, validate_template, warn_and_drop_long_samples, warn_completion_is_not_empty, warn_duplicated_rows, warn_imbalanced_completion, warn_low_n_samples, warn_missing_suffix
label_desc: Use image node_id 2 for calling a global function with example usage: test_warn_completion_is_not_empty() without return types