class_docstr: Intent classifier using simple keyword matching.
  
  The classifier takes a list of keywords and associated intents as an input.
  An input sentence is checked for the keywords and the intent is returned.
class_docstr_tok: ["Intent","classifier","using","simple","keyword","matching",".","The","classifier","takes","a","list","of","keywords","and","associated","intents","as","an","input",".","An","input","sentence","is","checked","for","the","keywords","and","the","intent","is","returned","."]
docstr: Loads trained component (see parent class for full docstring).
docstr_tok: ["Loads","trained","component","(","see","parent","class","for","full","docstring",")","."]
code: def load(
      cls,
      config: Dict[Text, Any],
      model_storage: ModelStorage,
      resource: Resource,
      execution_context: ExecutionContext,
      **kwargs: Any,
  ) -> KeywordIntentClassifier:
      """Loads trained component (see parent class for full docstring)."""
      try:
          with model_storage.read_from(resource) as model_dir:
              keyword_file = model_dir / f"{cls.__name__}.json"
              intent_keyword_map = rasa.shared.utils.io.read_json_file(
                  keyword_file
              )
      except ValueError:
          logger.warning(
              f"Failed to load {cls.__class__.__name__} from model storage. Resource "
              f"'{resource.name}' doesn't exist."
          )
          intent_keyword_map = None
  
      return cls(
          config,
          model_storage,
          resource,
          execution_context,
          intent_keyword_map,
      )
  
imports: from __future__ import annotations
  import logging
  import re
  from typing import Any, Dict, Optional, Text, List
  from rasa.engine.graph import GraphComponent, ExecutionContext
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.shared.constants import DOCS_URL_COMPONENTS
  from rasa.nlu.classifiers.classifier import IntentClassifier
  from rasa.shared.nlu.constants import INTENT, TEXT, INTENT_NAME_KEY, PREDICTED_CONFIDENCE_KEY
  import rasa.shared.utils.io
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.message import Message
label_desc: Use image node_id 9 for calling the KeywordIntentClassifier obj's underlying member method code with example usage: obj.load(cls, config, model_storage, resource, execution_context) and returns: cls