code: def from_recipe_config(cls, recipe_config, recipe_root):
      step_config = {}
      if (
          recipe_config.get("steps", {}).get("transform", {})
          is not None
      ):
          step_config.update(
              recipe_config.get("steps", {}).get("transform", {})
          )
      step_config["target_col"] = recipe_config.get("target_col")
      step_config["recipe"] = recipe_config.get(
          "recipe", "regression/v1"
      )
      if "positive_class" in recipe_config:
          step_config["positive_class"] = recipe_config.get(
              "positive_class"
          )
      step_config.update(
          get_recipe_tracking_config(
              recipe_root_path=recipe_root,
              recipe_config=recipe_config,
          ).to_dict()
      )
      return cls(step_config, recipe_root)
  
imports: import importlib
  import logging
  import os
  import sys
  import time
  import cloudpickle
  from packaging.version import Version
  from mlflow.exceptions import INVALID_PARAMETER_VALUE, MlflowException
  from mlflow.recipes.artifacts import DataframeArtifact, TransformerArtifact
  from mlflow.recipes.cards import BaseCard
  from mlflow.recipes.step import BaseStep, StepClass
  from mlflow.recipes.utils.execution import get_step_output_path
  from mlflow.recipes.utils.step import get_pandas_data_profiles, validate_classification_config
  from mlflow.recipes.utils.tracking import TrackingConfig, get_recipe_tracking_config
label_desc: Use image node_id 5 for calling the TransformStep obj's underlying member method code with example usage: obj.from_recipe_config(cls, recipe_config, recipe_root) and returns: cls