code: def validate_current_env_for_resampler(
      auto: bool = False,
  ) -> Optional[bool]:
      """
      Validate the current environment to check if it is a valid environment for plotly-resampler and if invalid trigger
      warning message.
  
      Parameters
      ----------
      auto: bool, optional
          If True, the function will automatically switch to a valid environment if the current environment is not valid.
          If False, the function will return None if the current environment is not valid.
      Returns
      -------
      bool :
          True if the current environment is a valid environment to run the code, False if the current environment is
          not a valid environment to run the code. None if the current environment is not a valid environment to run
          the code and the function did not switch to a valid environment.
      """
  
      from IPython import get_ipython
  
      if "google.colab" in str(get_ipython()):
          if auto:
              log_warning_resampler_switch_to_valid_env()
              valid_env = False
          else:
              log_warning_resampler_invalid_env()
              valid_env = None
      else:
          if is_notebook():
              valid_env = True
          else:
              if auto:
                  log_warning_resampler_switch_to_valid_env()
                  valid_env = False
              else:
                  log_warning_resampler_invalid_env()
                  valid_env = None
      return valid_env
  
file_path: neural_prophet/neuralprophet/plot_utils.py
imports: import logging
  import warnings
  from collections import OrderedDict
  from typing import Optional
  import numpy
  import torch
  from neuralprophet import time_dataset, utils_torch
label_desc: Use image node_id 9 for calling a global function with example usage: validate_current_env_for_resampler(auto) and returns: valid_env