(self, step, num_steps, learning_rate,
                        report_stats, multigpu=False)
return onmt.utils.Statistics()
This is the user-defined batch-level traing progress
        report function.

        Args:
            step(int): current step count.
            num_steps(int): total number of batches.
            learning_rate(float): current learning rate.
            report_stats(Statistics): old Statistics instance.
        Returns:
            report_stats(Statistics): updated Statistics instance.
This is the user-defined batch-level traing progress
        report function.
This is the user - defined batch - level traing progress report function .
def report_training(self, step, num_steps, learning_rate,
                        report_stats, multigpu=False):
        """
        This is the user-defined batch-level traing progress
        report function.

        Args:
            step(int): current step count.
            num_steps(int): total number of batches.
            learning_rate(float): current learning rate.
            report_stats(Statistics): old Statistics instance.
        Returns:
            report_stats(Statistics): updated Statistics instance.
        """
        if self.start_time < 0:
            raise ValueError("""ReportMgr needs to be started
                                (set 'start_time' or use 'start()'""")

        if multigpu:
            report_stats = onmt.utils.Statistics.all_gather_stats(report_stats)

        if step % self.report_every == 0:
            self._report_training(
                step, num_steps, learning_rate, report_stats)
            self.progress_step += 1
        return onmt.utils.Statistics()
def report_training ( self , step , num_steps , learning_rate , report_stats , multigpu = False ) : if self . start_time < 0 : raise ValueError ( """ReportMgr needs to be started
                                (set 'start_time' or use 'start()'""" ) if multigpu : report_stats = onmt . utils . Statistics . all_gather_stats ( report_stats ) if step % self . report_every == 0 : self . _report_training ( step , num_steps , learning_rate , report_stats ) self . progress_step += 1 return onmt . utils . Statistics ( )