code: def test_unused_future_regressors():
      df = pd.DataFrame(
          {
              "ds": {
                  0: "2022-10-16 00:00:00",
                  1: "2022-10-17 00:00:00",
                  2: "2022-10-18 00:00:00",
              },
              "y": {0: 17, 1: 18, 2: 10},
              "price": {0: 3.5, 1: 3.5, 2: 3.5},
              "cost": {0: 2.5, 1: 2.5, 2: 2.5},
          }
      )
      m = NeuralProphet(epochs=1, learning_rate=0.01)
      m.add_future_regressor("price")
      m.add_lagged_regressor("cost")
      m.fit(df, freq="D")
  
imports: import logging
  import math
  import os
  import pathlib
  import matplotlib.pyplot
  import numpy
  import pandas
  import pytest
  import torch
  from neuralprophet import NeuralProphet, df_utils, set_random_seed
  from neuralprophet.data.process import _handle_missing_data, _validate_column_name
label_desc: Use image node_id 43 for calling a global function with example usage: test_unused_future_regressors() without return types