code: def plot_tabular_models(
      results,
      output_directory=None,
      save_file="SummaryOfModels.html",
      plot_title="Models produced during fit()",
      show_plot=True,
  ):
      """Plot dynamic scatterplot of every single model trained during tabular_prediction.fit()
      Args:
          results:
              Dict created during TabularPredictor.fit_summary().
              Must at least contain key: 'model_performance'.
      """
      save_path = (
          output_directory + save_file if output_directory else None
      )
      hidden_keys = []
      model_performancedict = results["model_performance"]
      model_names = list(model_performancedict.keys())
      val_perfs = [model_performancedict[key] for key in model_names]
      model_types = [results["model_types"][key] for key in model_names]
      hidden_keys.append(model_types)
      model_hyperparams = [
          _formatDict(results["model_hyperparams"][key])
          for key in model_names
      ]
      datadict = {
          "performance": val_perfs,
          "model": model_names,
          "model_type": model_types,
          "hyperparameters": model_hyperparams,
      }
      leaderboard = results["leaderboard"].copy()
      leaderboard["fit_time"] = leaderboard["fit_time"].fillna(0)
      leaderboard["pred_time_val"] = leaderboard[
          "pred_time_val"
      ].fillna(0)
  
      datadict["inference_latency"] = [
          leaderboard["pred_time_val"][
              leaderboard["model"] == m
          ].values[0]
          for m in model_names
      ]
      datadict["training_time"] = [
          leaderboard["fit_time"][leaderboard["model"] == m].values[0]
          for m in model_names
      ]
      mousover_plot(
          datadict,
          attr_x="inference_latency",
          attr_y="performance",
          attr_color="model_type",
          save_file=save_path,
          plot_title=plot_title,
          hidden_keys=hidden_keys,
          show_plot=show_plot,
      )
  
file_path: autogluon/core/src/autogluon/core/utils/plots.py
imports: import os
  import warnings
  from collections import OrderedDict
  import numpy
  from .miscs import warning_filter
label_desc: Use image node_id 3 for calling a global function with example usage: plot_tabular_models(results, output_directory, save_file, plot_title, show_plot) without return types