code: def get_system_speed():
      repeats = 5
      benchmarks = np.array([])
      for a in range(0, repeats):
          start = time.time()
          for i in range(0, 1000):
              for x in range(1, 1000):
                  3.141592 * 2**x
              for x in range(1, 1000):
                  float(x) / 3.141592
              for x in range(1, 1000):
                  float(3.141592) / x
  
          end = time.time()
          duration = end - start
          duration = round(duration, 3)
          benchmarks = np.append(benchmarks, duration)
  
      log.info(f"System speed: {round(np.mean(benchmarks), 5)}s")
      log.info(f"Standart deviation: {round(np.std(benchmarks), 5)}s")
      return benchmarks.mean(), benchmarks.std()
  
file_path: neural_prophet/tests/test_model_performance.py
imports: import json
  import logging
  import os
  import pathlib
  import time
  import numpy
  import pandas
  import plotly.graph_objects
  from plotly.subplots import make_subplots
  from plotly_resampler import unregister_plotly_resampler
  from neuralprophet import NeuralProphet, set_random_seed
label_desc: Use image node_id 1 for calling a global function with example usage: get_system_speed() and returns: benchmarks,  benchmarks