def every_n_step_end(self, step, outputs):
    super(LoggingTrainable, self).every_n_step_end(step, outputs)
    stats = []
    for (tag, tensor_name) in six.iteritems(self._names):
        if (tensor_name in outputs):
            stats.append(('%s = %s' % (tag, str(_extract_output(outputs, tensor_name)))))
    logging.info('Logging Trainable: Step %d: %s', step, ', '.join(stats))
def every_n_step_end(self, step, outputs):
    super(LoggingTrainable, self).every_n_step_end(step, outputs)
    stats = []
    for (tag, tensor_name) in six.iteritems(self._names):
        if (tensor_name in outputs):
            stats.append(('%s = %s' % (tag, str(_extract_output(outputs, tensor_name)))))
    logging.info('Logging Trainable: Step %d: %s', step, ', '.join(stats))