code: def test_warning_incorrect_eval_num_examples(
      component_config: Dict[Text, Text]
  ):
      with pytest.warns(UserWarning) as record:
          train_utils._check_evaluation_setting(component_config)
          assert len(record) == 1
          assert (
              f"'{EVAL_NUM_EXAMPLES}' is not greater than 0. No checkpoint model "
              f"will be saved"
          ) in record[0].message.args[0]
  
imports: from typing import Any, Dict, List
  import numpy
  import pytest
  from typing import Text
  import rasa.utils.train_utils
  from rasa.nlu.constants import NUMBER_OF_SUB_TOKENS
  from rasa.nlu.tokenizers.tokenizer import Token
  from rasa.shared.nlu.constants import SPLIT_ENTITIES_BY_COMMA_DEFAULT_VALUE, SPLIT_ENTITIES_BY_COMMA
  from rasa.utils.tensorflow.constants import MODEL_CONFIDENCE, RANKING_LENGTH, RENORMALIZE_CONFIDENCES, SIMILARITY_TYPE, LOSS_TYPE, COSINE, SOFTMAX, INNER, CROSS_ENTROPY, MARGIN, AUTO, TOLERANCE, CHECKPOINT_MODEL, EVAL_NUM_EPOCHS, EVAL_NUM_EXAMPLES, EPOCHS
  from rasa.shared.exceptions import InvalidConfigException
label_desc: Use image node_id 11 for calling a global function with example usage: test_warning_incorrect_eval_num_examples(component_config) without return types