code: def _clean_model_results_labels(
      model_results: List[pd.DataFrame], model_labels: List[str]
  ) -> Tuple[List[pd.DataFrame], List[str]]:
      """Cleans the model results and names to remove models that did not produce
      any results, e.g. no residuals, insample predictions, etc.
  
      Parameters
      ----------
      model_results : List[pd.DataFrame]
          List of dataframes containing the model results (one dataframe per model)
          Some values might be None if the model did not produce a result. These
          will get dropped by this function.
      model_labels : List[str]
          The labels of the models producing the results.
  
      Returns
      -------
      Tuple[List[pd.DataFrame], List[str]]
          The cleaned model results and names (after removing those that did not
          produce a result).
      """
      includes = [
          True if model_result is not None else False
          for model_result in model_results
      ]
  
      # Remove None results (produced when insample or residuals can not be obtained)
      model_results = [
          model_result
          for include, model_result in zip(includes, model_results)
          if include
      ]
      model_labels = [
          model_name
          for include, model_name in zip(includes, model_labels)
          if include
      ]
  
      return model_results, model_labels
  
imports: from math import ceil
  from typing import Any, Dict, List, Optional, Tuple, Union
  import matplotlib
  import matplotlib.pyplot
  import numpy
  import pandas
  import plotly.express
  import plotly.graph_objects
  import plotly.io
  from plotly.colors import DEFAULT_PLOTLY_COLORS
  from plotly.subplots import make_subplots
  from scipy.fft import fft, fftfreq
  from scipy.signal import periodogram
  from statsmodels.graphics.gofplots import qqplot
  from statsmodels.tsa.seasonal import STL, seasonal_decompose
  from statsmodels.tsa.stattools import acf, ccf, pacf
  from pycaret.internal.logging import get_logger
  from pycaret.utils.generic import _resolve_dict_keys
  from pycaret.utils.time_series import TSAllowedPlotDataTypes
label_desc: Use image node_id 19 for calling a global function with example usage: _clean_model_results_labels(model_results, model_labels) and returns: model_results,  model_labels