如何使用张量板分析 keras 预测调用 [英] How to profile a keras predict call with tensorboard

问题描述

我想要预测调用的时间配置文件/跟踪，以估计我的模型执行推理的速度.

I would like to have a timing profile/trace of a predict call to get an estimate of how fast my model can perform inference.

现在我正在使用:

log_dir="logs/profile/" + datetime.datetime.now().strftime("%Y%m%d-%H%M%S")

tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, profile_batch = 1)

x_test, y_test = next(iter(training_ds))
_ = unet.predict(x_test, verbose=1, callbacks=[tensorboard_callback])

但是分析选项卡没有显示在张量板中.我在这里错过了什么?

But the profiling tab does not show up in tensorboard. What am I missing here?

推荐答案

如果您使用的是虚拟环境，请确保不要混淆.请参阅我对另一个问题的回答.

If you are using virtual environments, make sure you don't mix things up. See my answer to another question.

此外，有 4 种方法可以写入分析数据.正如您之前尝试过回调一样，您应该尝试其他方法:分析方法概述.

Also, there are 4 methods to write profiling data. As you tried callbacks before, you should give the other methods a try: Overview of profiling methods.

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