code: def _check_evaluation_setting(
      component_config: Dict[Text, Any]
  ) -> None:
      if (
          EVAL_NUM_EPOCHS in component_config
          and component_config[EVAL_NUM_EPOCHS] != -1
          and component_config[EVAL_NUM_EPOCHS]
          > component_config[EPOCHS]
      ):
          warning = (
              f"'{EVAL_NUM_EPOCHS}={component_config[EVAL_NUM_EPOCHS]}' is "
              f"greater than '{EPOCHS}={component_config[EPOCHS]}'."
              f" No evaluation will occur."
          )
          if component_config[CHECKPOINT_MODEL]:
              warning = (
                  f"You have opted to save the best model, but {warning} "
                  f"No checkpoint model will be saved."
              )
          rasa.shared.utils.io.raise_warning(warning)
      if (
          CHECKPOINT_MODEL in component_config
          and component_config[CHECKPOINT_MODEL]
      ):
          if (
              component_config[EVAL_NUM_EPOCHS] != -1
              and component_config[EVAL_NUM_EPOCHS] < 1
          ):
              rasa.shared.utils.io.raise_warning(
                  f"You have opted to save the best model, but the value of "
                  f"'{EVAL_NUM_EPOCHS}' is not -1 or greater than 0. Training will fail."
              )
          if (
              EVAL_NUM_EXAMPLES in component_config
              and component_config[EVAL_NUM_EXAMPLES] <= 0
          ):
              rasa.shared.utils.io.raise_warning(
                  f"You have opted to save the best model, but the value of "
                  f"'{EVAL_NUM_EXAMPLES}' is not greater than 0. No checkpoint model "
                  f"will be saved."
              )
  
imports: from pathlib import Path
  import numpy
  from typing import Optional, Text, Dict, Any, Union, List, Tuple, TYPE_CHECKING
  import rasa.shared.utils.common
  import rasa.shared.utils.io
  import rasa.nlu.utils.bilou_utils
  from rasa.shared.constants import NEXT_MAJOR_VERSION_FOR_DEPRECATIONS
  from rasa.nlu.constants import NUMBER_OF_SUB_TOKENS
  import rasa.utils.io
  from rasa.utils.tensorflow.constants import LOSS_TYPE, RANKING_LENGTH, RENORMALIZE_CONFIDENCES, SIMILARITY_TYPE, EVAL_NUM_EXAMPLES, EVAL_NUM_EPOCHS, EPOCHS, SOFTMAX, MARGIN, AUTO, INNER, COSINE, SEQUENCE, CROSS_ENTROPY, CONSTRAIN_SIMILARITIES, MODEL_CONFIDENCE, TOLERANCE, CHECKPOINT_MODEL
  from rasa.utils.tensorflow.callback import RasaTrainingLogger, RasaModelCheckpoint
  from rasa.utils.tensorflow.data_generator import RasaBatchDataGenerator
  from rasa.utils.tensorflow.model_data import RasaModelData
  from rasa.shared.nlu.constants import SPLIT_ENTITIES_BY_COMMA
  from rasa.shared.exceptions import InvalidConfigException
label_desc: Use image node_id 15 for calling a global function with example usage: _check_evaluation_setting(component_config) without return types