code: def test_minimal():
      log.info("testing: Plotting")
      df = pd.read_csv(PEYTON_FILE, nrows=NROWS)
      m = NeuralProphet(
          n_forecasts=7,
          n_lags=14,
          epochs=EPOCHS,
          batch_size=BATCH_SIZE,
          learning_rate=LR,
      )
      metrics_df = m.fit(df, freq="D", minimal=True)
      assert metrics_df is None
      m.predict(df)
  
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 34 for calling a global function with example usage: test_minimal() without return types