class_docstr: emotion keras solver 
class_docstr_tok: ["emotion","keras","solver"]
docstr: evaluation 
docstr_tok: ["evaluation"]
code: def eval(self):
      """evaluation"""
      # must first construct input data, then build model
      eval_ds, eval_task = self.input_data(mode=utils.EVAL)
      self.model_fn(mode=utils.EVAL)
      assert self._built
  
      callbacks = []
  
      self.active_model.evaluate_generator(
          eval_task,
          steps=len(eval_task),
          verbose=1,
          callbacks=callbacks,
          max_queue_size=20,
          workers=1,
          use_multiprocessing=False,
      )
  
      logging.info("Eval End.")
  
imports: import librosa
  from absl import logging
  import delta.compat
  from tensorflow.keras import backend
  from tensorflow.python.keras.utils import losses_utils
  from delta import utils
  from delta.utils.solver.estimator_solver import EstimatorSolver
  from delta.utils.solver.utils.callbacks import ClassReportCallBack
  from delta.utils.solver.asr_solver import AsrSolver
  from delta.utils.register import registers
label_desc: Use image node_id 6 for calling the EmoKerasSolver obj's underlying member method code with example usage: obj.eval() without return types