Debug Tensorflow的C++代码

栏目: C++ · 发布时间: 6年前

内容简介：单步调试python代码，直接用IDE就可以了(例如Intellij Idea). 但如果要跟踪C++代码，就要使用GDB(Linux使用GDB, Mac OS上要用LLDB).安装编译工具见:首先使用

单步调试 python 代码，直接用IDE就可以了(例如Intellij Idea). 但如果要跟踪C++代码，就要使用GDB(Linux使用GDB, Mac OS上要用LLDB).

准备工作

编译安装带调试信息的Tensorflow

安装编译工具见: https://www.tensorflow.org/install/source

首先使用 -c dbg 来编译安装tensorflow(以MacOS上编译tensorflow 1.8.0为例):

bazel build -c dbg //tensorflow/tools/pip_package:build_pip_package || exit 1
rm -rf /tmp/tf_pkg && bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tf_pkg || exit 1
pip uninstall -y tensorflow || exit 1
echo "Build Successful:" $(ls /tmp/tf_pkg)
pip install /tmp/tf_pkg/tensorflow-1.8.0-cp36-cp36m-macosx_10_13_x86_64.whl || exit 1

在Python脚本中加上中断

我们要在python加载 pywrap_tensorflow.so 之后用GDB/LLDB连上去, 所以为了让断点能生效，就在 import tensorflow 之后加个能让程序停下来的代码(应该还有别的方式，我目前还没发现). 例如:

import tensorflow as tf
import os

input("pid: " + str(os.getpid()) +", press enter to continue")

a = tf.constant([[1,3]])
b = tf.constant([[3],[1]])
c = tf.matmul(a, b)

with tf.Session() as sess:
    print(sess.run(c))

调试

使用GDB/LLDB 命令行

首先启动python程序:

$ python /tmp/test.py
pid: 44806, press enter to continue

我们看到pid是44806, 执行GDB/LLDB连上这个进程:

$ lldb -p 44806
(lldb) process attach --pid 44806
Process 44806 stopped
* thread #1, queue = 'com.apple.main-thread', stop reason = signal SIGSTOP
    frame #0: 0x00007fff707ecbea libsystem_kernel.dylib`__read_nocancel + 10
libsystem_kernel.dylib`__read_nocancel:
->  0x7fff707ecbea <+10>: jae    0x7fff707ecbf4            ; <+20>
    0x7fff707ecbec <+12>: movq   %rax, %rdi
    0x7fff707ecbef <+15>: jmp    0x7fff707e3ae9            ; cerror_nocancel
    0x7fff707ecbf4 <+20>: retq
Target 0: (Python) stopped.

Executable module set to "/Users/chi/.pyenv/versions/3.6.4/Python.framework/Versions/3.6/Resources/Python.app/Contents/MacOS/Python".
Architecture set to: x86_64h-apple-macosx.
(lldb)

此时Python程序已经被停下来了，接下来可以设置断点:

(lldb) breakpoint set -n TF_NewSession
Breakpoint 1: where = _pywrap_tensorflow_internal.so`::TF_NewSession(TF_Graph *, const TF_SessionOptions *, TF_Status *) + 31 at c_api.cc:2474, address = 0x000000011191246f
(lldb) breakpoint set -f matmul_op.cc -l 458
Breakpoint 2: 6 locations.
(lldb) breakpoint list
Current breakpoints:
1: name = 'TF_NewSession', locations = 1, resolved = 1, hit count = 0
  1.1: where = _pywrap_tensorflow_internal.so`::TF_NewSession(TF_Graph *, const TF_SessionOptions *, TF_Status *) + 31 at c_api.cc:2474, address = 0x000000011191246f, resolved, hit count = 0

2: file = 'matmul_op.cc', line = 458, exact_match = 0, locations = 6, resolved = 6, hit count = 0
  2.1: where = _pywrap_tensorflow_internal.so`tensorflow::MatMulOp<Eigen::ThreadPoolDevice, float, false>::Compute(tensorflow::OpKernelContext*) + 66 at matmul_op.cc:458, address = 0x0000000115428df2, resolved, hit count = 0
  2.2: where = _pywrap_tensorflow_internal.so`tensorflow::MatMulOp<Eigen::ThreadPoolDevice, double, false>::Compute(tensorflow::OpKernelContext*) + 66 at matmul_op.cc:458, address = 0x000000011547df42, resolved, hit count = 0
  2.3: where = _pywrap_tensorflow_internal.so`tensorflow::MatMulOp<Eigen::ThreadPoolDevice, Eigen::half, false>::Compute(tensorflow::OpKernelContext*) + 66 at matmul_op.cc:458, address = 0x00000001154d14d2, resolved, hit count = 0
  2.4: where = _pywrap_tensorflow_internal.so`tensorflow::MatMulOp<Eigen::ThreadPoolDevice, int, false>::Compute(tensorflow::OpKernelContext*) + 66 at matmul_op.cc:458, address = 0x0000000115524702, resolved, hit count = 0
  2.5: where = _pywrap_tensorflow_internal.so`tensorflow::MatMulOp<Eigen::ThreadPoolDevice, std::__1::complex<float>, false>::Compute(tensorflow::OpKernelContext*) + 66 at matmul_op.cc:458, address = 0x000000011557a962, resolved, hit count = 0
  2.6: where = _pywrap_tensorflow_internal.so`tensorflow::MatMulOp<Eigen::ThreadPoolDevice, std::__1::complex<double>, false>::Compute(tensorflow::OpKernelContext*) + 66 at matmul_op.cc:458, address = 0x00000001155d3a22, resolved, hit count = 0

设置了两个断点，第一个是 TF_NewSession 函数，第二个是 matmul_op.cc 的第458行. LLDB 的相关文档见 https://developer.apple.com/library/archive/documentation/General/Conceptual/lldb-guide/chapters/C3-Breakpoints.html .

接下来可以让程序继续运行. 在LLDB命令行下输入

(lldb) c
Process 44806 resuming

在python程序中按下回车, 可以看到LLDB已经运行到了断点, 进入了 TF_NewSession :

Process 44806 stopped
* thread #1, queue = 'com.apple.main-thread', stop reason = breakpoint 1.1
    frame #0: 0x000000011191246f _pywrap_tensorflow_internal.so`::TF_NewSession(graph=0x00007faaff47e310, opt=0x00007faafe87d530, status=0x00007faafc4dbc00) at c_api.cc:2474
   2471	TF_Session* TF_NewSession(TF_Graph* graph, const TF_SessionOptions* opt,
   2472	                          TF_Status* status) {
   2473	  Session* session;
-> 2474	  status->status = NewSession(opt->options, &session);
   2475	  if (status->status.ok()) {
   2476	    TF_Session* new_session = new TF_Session(session, graph);
   2477	    if (graph != nullptr) {
Target 0: (Python) stopped.

接下来就可以单步跟踪了。

使用IDE(VSCode)

GDB/LLDB只有命令行界面，使用比较麻烦，如果想用IDE可以使用VSCode.

安装插件

在MacOS上，需要运行

ln -s /Applications/Xcode.app/Contents/Developer/usr/bin/lldb-mi /usr/local/bin/lldb-mi

把 lldb-mi 放进 $PATH 里，才能和IDE进行连接。

首先安装一个叫 Native Debug 的插件: Debug Tensorflow的C++代码

然后点击debug标签下的配置按钮，创建一个debug配置(launch.json): Debug Tensorflow的C++代码

launch.json的内容如下:

{
    "version": "0.2.0",
    "configurations": [
        { 
            "name": "(lldb) Attach",
            "type": "cppdbg",
            "request": "attach",
            "program": "/Users/chi/.pyenv/versions/3.6.4/Python.framework/Versions/3.6/Resources/Python.app/Contents/MacOS/Python",
            "processId": "${command:pickProcess}",
            "MIMode": "lldb"
        },
    ]
}

设置断点

在VSCode里打开tensorflow代码目录，设置断点即可，例如: Debug Tensorflow的C++代码

进行调试

首先正常启动python程序:

$ python /tmp/test.py
pid: 45874, press enter to continue

然后在VSCode里点击运行按钮，运行刚才的”(lldb) Attach”: Debug Tensorflow的C++代码在输入框中找到目标python程序并点击(这里是python test.py的那个), 就可以进入调试模式. 进入python的窗口按下回车，让python程序继续运行，可以看到程序停在 TF_NewSession 函数上. 接下来就可以使用IDE中的按钮进行单步跟踪或者变量查看了。