code: def _validate_and_apply_step_config(self):
      required_configuration_keys = ["using", "location"]
      for key in required_configuration_keys:
          if key not in self.step_config:
              raise MlflowException(
                  f"The `{key}` configuration key must be specified for the predict step.",
                  error_code=INVALID_PARAMETER_VALUE,
              )
      if self.step_config["using"] not in {"parquet", "delta", "table"}:
          raise MlflowException(
              "Invalid `using` in predict step configuration.",
              error_code=INVALID_PARAMETER_VALUE,
          )
      if "model_uri" not in self.step_config:
          try:
              register_config = self.step_config["model_registry"]
              model_name = register_config["model_name"]
          except KeyError:
              raise MlflowException(
                  "No model specified for batch scoring: model_registry does not have "
                  "`model_uri` and does not have `model_name` configuration key.",
                  error_code=INVALID_PARAMETER_VALUE,
              )
          else:
              self.step_config[
                  "model_uri"
              ] = f"models:/{model_name}/latest"
      self.registry_uri = self.step_config.get("registry_uri", None)
      self.skip_data_profiling = self.step_config.get(
          "skip_data_profiling", False
      )
      self.save_mode = self.step_config.get("save_mode", "overwrite")
      self.run_end_time = None
      self.execution_duration = None
  
imports: import logging
  import os
  import time
  from typing import Any, Dict
  import mlflow
  from mlflow.exceptions import BAD_REQUEST, INVALID_PARAMETER_VALUE, MlflowException
  from mlflow.recipes.artifacts import DataframeArtifact, RegisteredModelVersionInfo
  from mlflow.recipes.cards import BaseCard
  from mlflow.recipes.step import BaseStep, StepClass
  from mlflow.recipes.steps.register import _REGISTERED_MV_INFO_FILE
  from mlflow.recipes.utils.execution import get_step_output_path
  from mlflow.recipes.utils.step import get_pandas_data_profiles
  from mlflow.recipes.utils.tracking import TrackingConfig, apply_recipe_tracking_config, get_recipe_tracking_config
  from mlflow.utils._spark_utils import _create_local_spark_session_for_recipes, _get_active_spark_session
  from mlflow.utils.databricks_utils import get_databricks_env_vars
  from mlflow.utils.file_utils import write_spark_dataframe_to_parquet_on_local_disk
label_desc: Use image node_id 2 for calling the PredictStep obj's underlying member method code with example usage: obj._validate_and_apply_step_config() without return types