class_docstr: Base class representing a step in an MLflow Recipe
docstr: Inspect the step output state by running the generic inspect information here and
  running the step specific inspection code in the step's _inspect() method.
  
  :param output_directory: String file path where to the directory where step
                           outputs are located.
  :return: None
docstr_tok: ["Inspect","the","step","output","state","by","running","the","generic","inspect","information","here","and","running","the","step","specific","inspection","code","in","the","step","'s","_inspect","(",")","method",".",":","param","output_directory",":","String","file","path","where","to","the","directory","where","step","outputs","are","located",".",":","return",":","None"]
code: def inspect(self, output_directory: str):
      """
      Inspect the step output state by running the generic inspect information here and
      running the step specific inspection code in the step's _inspect() method.
  
      :param output_directory: String file path where to the directory where step
                               outputs are located.
      :return: None
      """
      card_path = os.path.join(output_directory, CARD_PICKLE_NAME)
      if not os.path.exists(card_path):
          _logger.info(
              "Unable to locate runtime info for step '%s'. Re-run the step before inspect.",
              self.name,
          )
          return None
  
      card = BaseCard.load(card_path)
      card_html_path = os.path.join(output_directory, CARD_HTML_NAME)
      display_html(
          html_data=card.to_html(), html_file_path=card_html_path
      )
  
imports: import abc
  import json
  import logging
  import os
  import time
  import traceback
  from enum import Enum
  from typing import Any, Dict, List, Optional
  import yaml
  from mlflow.recipes.cards import CARD_HTML_NAME, CARD_PICKLE_NAME, BaseCard, FailureCard
  from mlflow.recipes.utils import get_recipe_name
  from mlflow.recipes.utils.step import display_html
  from mlflow.tracking import MlflowClient
  from mlflow.utils.databricks_utils import is_in_databricks_runtime
label_desc: Use image node_id 4 for calling the BaseStep obj's underlying member method code with example usage: obj.inspect(output_directory) and returns: None