如何解析tensorflow事件文件?

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问题描述

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我想知道如何从模型输出的 events 文件中提取与 Tensorboard 相同的性能结果:特别是精度、召回率和损失数字是最受关注的.这是给定模型检查点目录的 Tensorboard 上显示的其中一个子集:

I would like to know how to extract the same performance results from the events file of the output of a model as does Tensorboard : specifically the Precision, Recall, and Loss numbers are most of interest. Here is a subset of them displayed on Tensorboard given the model checkpoint directory:

我不确定是否有可用于这些模型的自记录信息或其他元数据.这个特别是 Faster RNN Inception:但这些输出是绑定到特定模型还是格式通用?

I'm not sure if there self-documenting information or other metadata available for these models. This one in particular is the Faster RNN Inception: but are these outputs tied to a particular model or are they generic in format?

推荐答案

在 tensorboard 包中找到方法:

  from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
  event_acc = EventAccumulator(evtf)
  event_acc.Reload()

其中一个条目是:

  scal_losses = event_acc.Scalars('Loss/total_loss')

从该列表中，我们可以提取诸如 Step [number] 和 Value(loss)之类的属性:

From that list we can extract such attributes as Step [number] and Value (of the loss):

 losses = sorted([[sevt.step, sevt.value] for sevt in scal_losses])

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