从tensorflow_cc和tensorflow_framework生成静态库 [英] Produce static libs from tensorflow_cc and tensorflow_framework

问题描述

据我了解，使用bazel只能产生libtensorflow_cc.so和libtensorflow_framework.so. 我需要生成独立于位置(-fPIC)的静态库，因为稍后将它们链接到我自己的动态库中.

As far as I understand using bazel I can only produce libtensorflow_cc.so and libtensorflow_framework.so. I need to produce static libs that are position independent (-fPIC) because I'll link them to a dynamic lib of my own later.

我找到了此答案，它建议使用项目中包含的Makefile. 我成功地用它代替了libtensorflow_cc.so，但是我该怎么做来代替libtensorflow_framework.so?

I found this answer which suggest the use of a Makefile included in the project. I successfully used it to replace the libtensorflow_cc.so but what can I do to replace libtensorflow_framework.so?

推荐答案

不是实际答案，但评论太长.

Not an actual answer, but too long for a comment.

我设法在Windows上使用Bazel做类似您提到的事情.特别是，我想制作一个带有一个或两个标头(在功能上受限制)的包装器DLL，这样我就可以轻松移动.我将总结自己所做的事情；它相当复杂，可以满足我们的需求，但是也许您会发现有用的东西.

I managed to do something like what you mention using Bazel on Windows. In particular, I wanted to make a single wrapper DLL with one or two headers (limited in functionality) that I could move around easily. I'll write a summary of the things that I did; it's rather convoluted an customized for our needs, but maybe you find something useful.

• 我将--config=monolithic传递给bazel build命令(除了您需要的任何其他选项).这样可以避免对库进行模块化，从而消除对libtensorflow_framework.so的依赖(请参阅 工具/bazel.rc ).
• 我建立的目标不是TensorFlow信息库中的任何目标.相反，我添加了一个非常小的程序，该程序将包装器用作新的Bazel目标(一个C ++文件以及我的标头标头和BUILD文件).因此，必须预先编译所有TensorFlow才能编译此最终的虚拟程序.
• 完成这些工作后，我利用了Bazel已经将每个子目标编译为静态库这一事实.我检查为我的虚拟程序目标生成的bazel-bin目录下的文件，文件名称的结尾为.params-在这里找到用于编译该文件的所有静态库的路径.
• 我将所有这些中间静态库复制到其他地方.另外，我复制了一堆标头，我将需要编译我的最终包装器(TensorFlow自己的包装器，现在也包括Eigen，Protobuf和Nsync).我把所有这些都放在我之前准备的构建区域中.
• 我使用NMake Makefile通过静态库，复制的标头和我自己的薄包装器来生成我的自定义DLL.

• I pass --config=monolithic to the bazel build command (besides any other option that you need). That will avoid modularizing the library and thus remove the dependency to a libtensorflow_framework.so (see tools/bazel.rc).
• The goal that I build is not any of the ones in the TensorFlow repository. Instead, I add a very small program that uses my wrapper as a new Bazel target (a C++ file plus my headers headers and a BUILD file). So all of TensorFlow had to be compiled beforehand in order to compile this final dummy program.
• When I get that done, I take advantage of the fact that Bazel does already compile every subgoal as a static library. I check a file under the bazel-bin directory generated for my dummy program goal with a name ending .params - there I find the path of all the static libraries that were used to compile it.
• I copy all of these intermediate static libraries to somewhere else. Also, I copy a bunch of headers I will need to compile my final wrapper (TensorFlow own's, but also Eigen, Protobuf and Nsync now too). I put all of this in a build area I have prepared before.
• I use NMake Makefile to produce my custom DLL, using the static libraries, the copied headers and my own thin wrapper.

就是这样，我想.我在MSYS2上运行一个丑陋的Bash脚本，可以为我做所有事情.通常，对于每个新发行版，我都需要调整一两个内容(configure脚本中的某些选项，我需要复制一些其他头文件，等等)，但最终还是可以使它起作用.但是，这很麻烦，所以我不一定要说您应该使用相同的方法(但是，如果需要，可以随时询问有关任何步骤的详细信息).

And that's about it, I think. I have an ugly Bash script I run on MSYS2 that does everything for me. Usually with every new release I need to tweak one or two things (some option in the configure script, some additional headers I need to copy, etc.), but I do get it to work in the end. It's quite a lot of fiddling though, so I'm not necessarily saying you should use the same approach (but feel free to ask for details about any step if you want).

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