trainer.py 文件源码

def optimize(self, data, with_metrics=False, with_trace=False):
        """ Optimize a single batch """
        run_metadata = tf.RunMetadata() if with_trace else None
        trace = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE) if with_trace else None

        _, metrics = self.run(
            self.training_operation, data,
            run_options=trace, run_metadata=run_metadata)

        if with_metrics:
            self.timer_update()
            steps, elapsed = self.elapsed()
            num_devices = len(self.towers)
            examples = steps * self.batch_size * num_devices
            print('Step {}, examples/sec {:.3f}, ms/batch {:.1f}'.format(
                self.global_step, examples / elapsed, 1000 * elapsed / num_devices))

            self.output_metrics(data, metrics)
            self.write_summaries(data)

        if with_trace:
            step = '{}/step{}'.format(self.name, self.global_step)
            self.summary_writer.add_run_metadata(run_metadata, step, global_step=self.global_step)