class_docstr: Base class to transform the dialogue state into an ML format.
  
  Subclasses of SingleStateFeaturizer will decide how a bot will
  transform the dialogue state into a dictionary mapping an attribute
  to its features. Possible attributes are: `INTENT`, `TEXT`, `ACTION_NAME`,
  `ACTION_TEXT`, `ENTITIES`, `SLOTS` and `ACTIVE_LOOP`. Each attribute will be
  featurized into a list of `rasa.utils.features.Features`.
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code: def _state_features_for_attribute(
      self, sub_state: SubState, attribute: Text
  ) -> Dict[Text, int]:
      # FIXME: the code below is not type-safe, but fixing it
      #        would require more refactoring, for instance using
      #        data classes in our states
      if attribute in {INTENT, ACTION_NAME}:
          return {sub_state[attribute]: 1}  # type: ignore[dict-item]
      elif attribute == ENTITIES:
          return {entity: 1 for entity in sub_state.get(ENTITIES, [])}  # type: ignore[misc]  # noqa: E501
      elif attribute == ACTIVE_LOOP:
          return {sub_state["name"]: 1}  # type: ignore[dict-item]
      elif attribute == SLOTS:
          return {
              f"{slot_name}_{i}": value  # type: ignore[misc]
              for slot_name, slot_as_feature in sub_state.items()
              for i, value in enumerate(slot_as_feature)
          }
      else:
          raise ValueError(
              f"Given attribute '{attribute}' is not supported. "
              f"It must be one of '{self._default_feature_states.keys()}'."
          )
  
imports: import logging
  import numpy
  import scipy.sparse
  from typing import List, Optional, Dict, Text, Set, Any
  from rasa.core.featurizers.precomputation import MessageContainerForCoreFeaturization
  from rasa.nlu.extractors.extractor import EntityTagSpec
  from rasa.nlu.utils import bilou_utils
  from rasa.nlu.utils.bilou_utils import BILOU_PREFIXES
  from rasa.shared.core.domain import SubState, State, Domain
  from rasa.shared.core.constants import PREVIOUS_ACTION, ACTIVE_LOOP, USER, SLOTS
  from rasa.shared.core.trackers import is_prev_action_listen_in_state
  from rasa.shared.nlu.constants import ENTITIES, FEATURE_TYPE_SENTENCE, ACTION_TEXT, ACTION_NAME, INTENT, NO_ENTITY_TAG, ENTITY_ATTRIBUTE_TYPE, ENTITY_TAGS, TEXT
  from rasa.shared.nlu.training_data.features import Features
  from rasa.utils.tensorflow import model_data_utils
label_desc: Use image node_id 4 for calling the SingleStateFeaturizer obj's underlying member method code with example usage: obj._state_features_for_attribute(sub_state, attribute) and returns: dict, unknown, dict, unknown