class_docstr: Recipe which converts the normal model config to train and predict graph.
class_docstr_tok: ["Recipe","which","converts","the","normal","model","config","to","train","and","predict","graph","."]
docstr: Determine configuration from auto-filled configuration file.
  
  Keys that are provided and have a value in the file are kept. Keys that are not
  provided are configured automatically.
  
  Note that this needs to be called explicitly; ie. we cannot
  auto-configure automatically from importers because importers are not
  allowed to access code outside of `rasa.shared`.
  
  Args:
      config_file_path: The path to the configuration file.
      config: Configuration in dictionary format.
      training_type: Optional training type to auto-configure. By default
      both core and NLU will be auto-configured.
code: def auto_configure(
      config_file_path: Optional[Text],
      config: Dict,
      training_type: Optional[TrainingType] = TrainingType.BOTH,
  ) -> Tuple[Dict[Text, Any], Set[str], Set[str]]:
      """Determine configuration from auto-filled configuration file.
  
      Keys that are provided and have a value in the file are kept. Keys that are not
      provided are configured automatically.
  
      Note that this needs to be called explicitly; ie. we cannot
      auto-configure automatically from importers because importers are not
      allowed to access code outside of `rasa.shared`.
  
      Args:
          config_file_path: The path to the configuration file.
          config: Configuration in dictionary format.
          training_type: Optional training type to auto-configure. By default
          both core and NLU will be auto-configured.
      """
      missing_keys = DefaultV1Recipe._get_missing_config_keys(
          config, training_type
      )
      keys_to_configure = (
          DefaultV1Recipe._get_unspecified_autoconfigurable_keys(
              config, training_type
          )
      )
  
      if keys_to_configure:
          config = DefaultV1Recipe.complete_config(
              config, keys_to_configure
          )
          DefaultV1Recipe._dump_config(
              config,
              config_file_path,
              missing_keys,
              keys_to_configure,
              training_type,
          )
  
      return config, missing_keys, keys_to_configure
  
imports: from __future__ import annotations
  import copy
  import enum
  import logging
  import math
  from enum import Enum
  from typing import Dict, Text, Any, Tuple, Type, Optional, List, Callable, Set, Union
  import dataclasses
  from rasa.core.featurizers.precomputation import CoreFeaturizationInputConverter, CoreFeaturizationCollector
  from rasa.plugin import plugin_manager
  from rasa.shared.exceptions import FileNotFoundException
  from rasa.core.policies.ensemble import DefaultPolicyPredictionEnsemble
  from rasa.engine.graph import GraphSchema, GraphComponent, SchemaNode, GraphModelConfiguration
  from rasa.engine.constants import PLACEHOLDER_IMPORTER, PLACEHOLDER_MESSAGE, PLACEHOLDER_TRACKER
  from rasa.engine.recipes.recipe import Recipe
  from rasa.engine.storage.resource import Resource
  from rasa.graph_components.converters.nlu_message_converter import NLUMessageConverter
  from rasa.graph_components.providers.domain_provider import DomainProvider
  from rasa.graph_components.providers.forms_provider import FormsProvider
  from rasa.graph_components.providers.responses_provider import ResponsesProvider
  from rasa.graph_components.providers.domain_for_core_training_provider import DomainForCoreTrainingProvider
  from rasa.graph_components.providers.nlu_training_data_provider import NLUTrainingDataProvider
  from rasa.graph_components.providers.rule_only_provider import RuleOnlyDataProvider
  from rasa.graph_components.providers.story_graph_provider import StoryGraphProvider
  from rasa.graph_components.providers.training_tracker_provider import TrainingTrackerProvider
  import rasa.shared.constants
  from rasa.shared.exceptions import RasaException, InvalidConfigException
  from rasa.shared.constants import ASSISTANT_ID_KEY
  from rasa.shared.data import TrainingType
  from rasa.utils.tensorflow.constants import EPOCHS
  from rasa.shared.utils.common import class_from_module_path, transform_collection_to_sentence
label_desc: Use image node_id 20 for calling the DefaultV1Recipe obj's underlying member method code with example usage: obj.auto_configure(config_file_path, config, training_type) and returns: config,  missing_keys,  keys_to_configure