parameters: (self, delay_secs=None)
return_statement: return self._estimator.evaluate(input_fn=self._eval_input_fn,
                                      steps=self._eval_steps,
                                      metrics=self._eval_metrics,
                                      name="one_pass")
docstring: Evaluate on the evaluation data.
  
      Runs evaluation on the evaluation data and returns the result. Runs for
      `self._eval_steps` steps, or if it's `None`, then run until input is
      exhausted or another exception is raised. Start the evaluation after
      `delay_secs` seconds, or if it's `None`, defaults to using
      `self._eval_delay_secs` seconds.
  
      Args:
        delay_secs: Start evaluating after this many seconds. If `None`, defaults
          to using `self._eval_delays_secs`.
  
      Returns:
        The result of the `evaluate` call to the `Estimator`.
docstring_summary: Evaluate on the evaluation data.
docstring_tokens: Evaluate on the evaluation data .
function: def evaluate(self, delay_secs=None):
      """Evaluate on the evaluation data.
  
      Runs evaluation on the evaluation data and returns the result. Runs for
      `self._eval_steps` steps, or if it's `None`, then run until input is
      exhausted or another exception is raised. Start the evaluation after
      `delay_secs` seconds, or if it's `None`, defaults to using
      `self._eval_delay_secs` seconds.
  
      Args:
        delay_secs: Start evaluating after this many seconds. If `None`, defaults
          to using `self._eval_delays_secs`.
  
      Returns:
        The result of the `evaluate` call to the `Estimator`.
      """
      if delay_secs is None:
        delay_secs = self._eval_delay_secs
  
      if delay_secs:
        logging.info("Waiting %d secs before starting eval.", delay_secs)
        time.sleep(delay_secs)
  
      return self._estimator.evaluate(input_fn=self._eval_input_fn,
                                      steps=self._eval_steps,
                                      metrics=self._eval_metrics,
                                      name="one_pass")
function_tokens: def evaluate ( self , delay_secs = None ) : if delay_secs is None : delay_secs = self . _eval_delay_secs if delay_secs : logging . info ( "Waiting %d secs before starting eval." , delay_secs ) time . sleep ( delay_secs ) return self . _estimator . evaluate ( input_fn = self . _eval_input_fn , steps = self . _eval_steps , metrics = self . _eval_metrics , name = "one_pass" )