class_docstr: infer from forzen model 
class_docstr_tok: ["infer","from","forzen","model"]
docstr: infer prediction results and/or log metrics 
docstr_tok: ["infer","prediction","results","and\/or","log","metrics"]
code: def predict(self):
      """infer prediction results and/or log metrics"""
      batch = 0
      try:
          while True:
              batch += 1
              logging.info("process {} batches".format(batch))
              y_pred, y_true = self.run()
              if self._mode == utils.EVAL:
                  self.metric(y_pred, y_true)
      except tf.errors.OutOfRangeError:
          logging.info("Process End")
  
      if self._mode == utils.EVAL:
          acc, precision, recall = self.metric.result()
          logging.info("acc {}".format(acc))
          logging.info("precision {}".format(precision))
          logging.info("recall {}".format(recall))
  
imports: import numpy
  from absl import logging
  import delta.compat
  from delta import utils
  from delta.utils.register import registers
  from delta.utils.register import import_all_modules_for_register
  from delta.serving.base_frozen_model import Evaluater
label_desc: Use image node_id 2 for calling the EmoSpeechEvaluater obj's underlying member method code with example usage: obj.predict() without return types