在Caffe中是否可以计算在架构中进行的操作数量？ [英] Is it possible in Caffe to calculate number of Operations taking place in an architecture?

问题描述

我在 tensorflow教程中已经看到，它们提供了有关不同架构的一些有趣统计数据，例如发生的操作次数等。

I have seen in tensorflow tutorials, they provide some interesting statistics about different architectures, such as number of operations taking place, etc .

此模型在
的GPU训练时间之内，可以达到约86％的准确度。请参见下面以及
详细信息的代码。它包含1,068,298个可学习的参数，并且需要
约1950万次乘法运算来计算单个
图像上的推断。

This model achieves a peak performance of about 86% accuracy within a few hours of training time on a GPU. Please see below and the code for details. It consists of 1,068,298 learnable parameters and requires about 19.5M multiply-add operations to compute inference on a single image.

如何使用Caffe实现类似的功能？

我自己如何计算或编译这些有趣的统计信息？

（顺便说一句，我不是在谈论张量板可视化，只是统计信息，例如操作数和类似的东西）

How can I achieve something similar using Caffe?
How can compute or compile such interesting statistics myself?
(by the way I'm not talking about tensorboard visualizations, Just statistics such as number of operations and stuff like that)

推荐答案

有一个开放的 issue＃2507 。

我们非常欢迎您提出一个实现此功能对caffe的贡献！

There is an open issue #2507 in BVLC/caffe github requesting this feature.
You are more than welcome to make a contribution to caffe implementing this feature!

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