class_docstr: Base Recipe
class_docstr_tok: ["Base","Recipe"]
docstr: Returns absolute path to the recipe DAG representation HTML file.
docstr_tok: ["Returns","absolute","path","to","the","recipe","DAG","representation","HTML","file","."]
code: def _get_recipe_dag_file(self) -> str:
      """
      Returns absolute path to the recipe DAG representation HTML file.
      """
      import jinja2
  
      j2_env = jinja2.Environment(
          loader=jinja2.FileSystemLoader(os.path.dirname(__file__))
      )
      recipe_dag_template = j2_env.get_template(
          "resources/recipe_dag_template.html"
      ).render(
          {
              "recipe_yaml_help": {
                  "help_string_type": "yaml",
                  "help_string": dag_help_strings.RECIPE_YAML,
              },
              "ingest_step_help": {
                  "help_string": dag_help_strings.INGEST_STEP,
                  "help_string_type": "text",
              },
              "ingest_user_code_help": {
                  "help_string": dag_help_strings.INGEST_USER_CODE,
                  "help_string_type": "python",
              },
              "ingested_data_help": {
                  "help_string": dag_help_strings.INGESTED_DATA,
                  "help_string_type": "text",
              },
              "split_step_help": {
                  "help_string": dag_help_strings.SPLIT_STEP,
                  "help_string_type": "text",
              },
              "split_user_code_help": {
                  "help_string": dag_help_strings.SPLIT_USER_CODE,
                  "help_string_type": "python",
              },
              "training_data_help": {
                  "help_string": dag_help_strings.TRAINING_DATA,
                  "help_string_type": "text",
              },
              "validation_data_help": {
                  "help_string": dag_help_strings.VALIDATION_DATA,
                  "help_string_type": "text",
              },
              "test_data_help": {
                  "help_string": dag_help_strings.TEST_DATA,
                  "help_string_type": "text",
              },
              "transform_step_help": {
                  "help_string": dag_help_strings.TRANSFORM_STEP,
                  "help_string_type": "text",
              },
              "transform_user_code_help": {
                  "help_string": dag_help_strings.TRANSFORM_USER_CODE,
                  "help_string_type": "python",
              },
              "fitted_transformer_help": {
                  "help_string": dag_help_strings.FITTED_TRANSFORMER,
                  "help_string_type": "text",
              },
              "transformed_training_and_validation_data_help": {
                  "help_string": dag_help_strings.TRANSFORMED_TRAINING_AND_VALIDATION_DATA,
                  "help_string_type": "text",
              },
              "train_step_help": {
                  "help_string": dag_help_strings.TRAIN_STEP,
                  "help_string_type": "text",
              },
              "train_user_code_help": {
                  "help_string": dag_help_strings.TRAIN_USER_CODE,
                  "help_string_type": "python",
              },
              "fitted_model_help": {
                  "help_string": dag_help_strings.FITTED_MODEL,
                  "help_string_type": "text",
              },
              "mlflow_run_help": {
                  "help_string": dag_help_strings.MLFLOW_RUN,
                  "help_string_type": "text",
              },
              "predicted_training_data_help": {
                  "help_string": dag_help_strings.PREDICTED_TRAINING_DATA,
                  "help_string_type": "text",
              },
              "custom_metrics_user_code_help": {
                  "help_string": dag_help_strings.CUSTOM_METRICS_USER_CODE,
                  "help_string_type": "python",
              },
              "evaluate_step_help": {
                  "help_string": dag_help_strings.EVALUATE_STEP,
                  "help_string_type": "text",
              },
              "model_validation_status_help": {
                  "help_string": dag_help_strings.MODEL_VALIDATION_STATUS,
                  "help_string_type": "text",
              },
              "register_step_help": {
                  "help_string": dag_help_strings.REGISTER_STEP,
                  "help_string_type": "text",
              },
              "registered_model_version_help": {
                  "help_string": dag_help_strings.REGISTERED_MODEL_VERSION,
                  "help_string_type": "text",
              },
              "ingest_scoring_step_help": {
                  "help_string": dag_help_strings.INGEST_SCORING_STEP,
                  "help_string_type": "text",
              },
              "ingested_scoring_data_help": {
                  "help_string": dag_help_strings.INGESTED_SCORING_DATA,
                  "help_string_type": "text",
              },
              "predict_step_help": {
                  "help_string": dag_help_strings.PREDICT_STEP,
                  "help_string_type": "text",
              },
              "scored_data_help": {
                  "help_string": dag_help_strings.SCORED_DATA,
                  "help_string_type": "text",
              },
          }
      )
  
      recipe_dag_file = os.path.join(
          get_or_create_base_execution_directory(
              self._recipe_root_path
          ),
          "recipe_dag.html",
      )
      with open(recipe_dag_file, "w") as f:
          f.write(recipe_dag_template)
  
      return recipe_dag_file
  
imports: import abc
  import logging
  import os
  from typing import List, Optional
  from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import BAD_REQUEST, INTERNAL_ERROR, INVALID_PARAMETER_VALUE
  from mlflow.recipes import dag_help_strings
  from mlflow.recipes.artifacts import Artifact
  from mlflow.recipes.step import BaseStep, StepClass, StepStatus
  from mlflow.recipes.utils import get_recipe_config, get_recipe_name, get_recipe_root_path
  from mlflow.recipes.utils.execution import clean_execution_state, get_or_create_base_execution_directory, get_step_output_path, run_recipe_step
  from mlflow.recipes.utils.step import display_html
  from mlflow.utils.class_utils import _get_class_from_string
label_desc: Use image node_id 11 for calling the BaseRecipe obj's underlying member method code with example usage: obj._get_recipe_dag_file() and returns: recipe_dag_file