code: def pretrained_embeddings_spacy_config() -> Dict:
      return {
          "assistant_id": "placeholder_default",
          "language": "en",
          "pipeline": [
              {"name": "SpacyNLP", "model": "en_core_web_md"},
              {"name": "SpacyTokenizer"},
              {"name": "SpacyFeaturizer"},
              {"name": "RegexFeaturizer"},
              {
                  "name": "CRFEntityExtractor",
                  EPOCHS: 1,
                  RANDOM_SEED: 42,
              },
              {"name": "EntitySynonymMapper"},
              {"name": "SklearnIntentClassifier"},
          ],
      }
  
file_path: rasa/tests/nlu/conftest.py
imports: import copy
  from typing import Any, Callable, Dict, List, Text, Tuple, Type, Union
  import pytest
  from rasa.engine.graph import ExecutionContext, GraphComponent, GraphSchema
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.nlu.featurizers.dense_featurizer.spacy_featurizer import SpacyFeaturizer
  from rasa.nlu.tokenizers.mitie_tokenizer import MitieTokenizer
  from rasa.nlu.tokenizers.spacy_tokenizer import SpacyTokenizer
  from rasa.shared.importers.rasa import RasaFileImporter
  from rasa.shared.nlu.training_data.message import Message
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.utils.tensorflow.constants import EPOCHS, RANDOM_SEED
label_desc: Use image node_id 1 for calling a global function with example usage: pretrained_embeddings_spacy_config() and returns: dict