code: def test_reg_func_abs():
      log.info("testing: reg func abs")
      assert pytest.approx(1) == reg_func_abs(torch.Tensor([1]))
      assert pytest.approx(0) == reg_func_abs(torch.Tensor([0]))
      assert pytest.approx(1) == reg_func_abs(torch.Tensor([-1]))
  
      assert pytest.approx(1) == reg_func_abs(torch.Tensor([1, 1, 1]))
      assert pytest.approx(0) == reg_func_abs(torch.Tensor([0, 0, 0]))
      assert pytest.approx(1) == reg_func_abs(
          torch.Tensor([-1, -1, -1])
      )
  
      assert pytest.approx(0.6666666) == reg_func_abs(
          torch.Tensor([-1, 0, 1])
      )
      assert pytest.approx(20) == reg_func_abs(
          torch.Tensor([-12, 4, 0, -1, 1, 102])
      )
  
file_path: neural_prophet/tests/test_regularization.py
imports: import logging
  import random
  import numpy
  import pandas
  import pytest
  import torch
  from neuralprophet import NeuralProphet, df_utils
  from neuralprophet.utils import reg_func_abs
  from tests.utils.dataset_generators import generate_event_dataset, generate_holiday_dataset, generate_lagged_regressor_dataset
label_desc: Use image node_id 1 for calling a global function with example usage: test_reg_func_abs() without return types