class_docstr: Extracts entities via lookup tables and regexes defined in the training data.
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,
  ) -> RegexEntityExtractor:
      """Loads trained component (see parent class for full docstring)."""
      try:
          with model_storage.read_from(resource) as model_path:
              regex_file = model_path / cls.REGEX_FILE_NAME
              patterns = rasa.shared.utils.io.read_json_file(regex_file)
              return cls(
                  config,
                  model_storage=model_storage,
                  resource=resource,
                  patterns=patterns,
              )
      except (ValueError, FileNotFoundError):
          rasa.shared.utils.io.raise_warning(
              f"Failed to load {cls.__name__} from model storage. "
              f"This can happen if the model could not be trained because regexes "
              f"could not be extracted from the given training data - and hence "
              f"could not be persisted."
          )
          return cls(
              config, model_storage=model_storage, resource=resource
          )
  
imports: from __future__ import annotations
  import logging
  import re
  from typing import Any, Dict, List, Optional, Text
  from rasa.engine.graph import GraphComponent, ExecutionContext
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.storage.storage import ModelStorage
  from rasa.engine.storage.resource import Resource
  import rasa.shared.utils.io
  import rasa.nlu.utils.pattern_utils
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.message import Message
  from rasa.shared.nlu.constants import ENTITIES, ENTITY_ATTRIBUTE_VALUE, ENTITY_ATTRIBUTE_START, ENTITY_ATTRIBUTE_END, TEXT, ENTITY_ATTRIBUTE_TYPE
  from rasa.nlu.extractors.extractor import EntityExtractorMixin
label_desc: Use image node_id 7 for calling the RegexEntityExtractor obj's underlying member method code with example usage: obj.load(cls, config, model_storage, resource, execution_context) and returns: cls, cls