code: def test_check_duplicate_ds():
      # Check whether a ValueError is thrown in case there
      # are duplicate dates in the ds column of dataframe
      df = pd.read_csv(PEYTON_FILE, nrows=102)[:50]
      # introduce duplicates in dataframe
      df = pd.concat([df, df[8:9]]).reset_index()
      # Check if error thrown on duplicates
      m = NeuralProphet(
          epochs=EPOCHS,
          batch_size=BATCH_SIZE,
          learning_rate=LR,
          n_lags=24,
          ar_reg=0.5,
      )
      with pytest.raises(ValueError):
          m.fit(df, freq="D")
  
imports: import logging
  import os
  import pathlib
  import matplotlib.pyplot
  import numpy
  import pandas
  import pytest
  from torch.utils.data import DataLoader
  from neuralprophet import NeuralProphet, configure, df_utils, time_dataset
  from neuralprophet.data.process import _create_dataset, _handle_missing_data
  from neuralprophet.data.transform import _normalize
label_desc: Use image node_id 11 for calling a global function with example usage: test_check_duplicate_ds() without return types