code: def test_save_load():
      df = pd.read_csv(PEYTON_FILE, nrows=NROWS)
      m = NeuralProphet(
          epochs=EPOCHS,
          batch_size=BATCH_SIZE,
          learning_rate=LR,
          n_lags=6,
          n_forecasts=3,
          n_changepoints=0,
      )
      _ = m.fit(df, freq="D")
      future = m.make_future_dataframe(df, periods=3)
      forecast = m.predict(df=future)
      log.info("testing: save")
      save(m, "test_model.pt")
  
      log.info("testing: load")
      m2 = load("test_model.pt")
      forecast2 = m2.predict(df=future)
  
      m3 = load("test_model.pt", map_location="cpu")
      forecast3 = m3.predict(df=future)
  
      # Check that the forecasts are the same
      pd.testing.assert_frame_equal(forecast, forecast2)
      pd.testing.assert_frame_equal(forecast, forecast3)
  
file_path: neural_prophet/tests/test_utils.py
imports: import logging
  import os
  import pathlib
  import pandas
  import pytest
  from neuralprophet import NeuralProphet, df_utils, load, save
label_desc: Use image node_id 2 for calling a global function with example usage: test_save_load() without return types