首先，您应该按照这里的说明从Github下载源代码(您需要Bazel和最新版本的GCC)。

The C++ API (and the backend of the system) is in tensorflow/core. Right now, only the C++ Session interface, and the C API are being supported. You can use either of these to execute TensorFlow graphs that have been built using the Python API and serialized to a GraphDef protocol buffer. There is also an experimental feature for building graphs in C++, but this is currently not quite as full-featured as the Python API (e.g. no support for auto-differentiation at present). You can see an example program that builds a small graph in C++ here.

c++ API的第二部分是用于添加新的OpKernel的API，这是一个包含CPU和GPU的数值内核实现的类。在tensorflow/core/kernels中有许多如何构建这些操作的示例，以及在c++中添加新操作的教程。

首先，您应该按照这里的说明从Github下载源代码(您需要Bazel和最新版本的GCC)。

The C++ API (and the backend of the system) is in tensorflow/core. Right now, only the C++ Session interface, and the C API are being supported. You can use either of these to execute TensorFlow graphs that have been built using the Python API and serialized to a GraphDef protocol buffer. There is also an experimental feature for building graphs in C++, but this is currently not quite as full-featured as the Python API (e.g. no support for auto-differentiation at present). You can see an example program that builds a small graph in C++ here.

c++ API的第二部分是用于添加新的OpKernel的API，这是一个包含CPU和GPU的数值内核实现的类。在tensorflow/core/kernels中有许多如何构建这些操作的示例，以及在c++中添加新操作的教程。

为了补充@mrry的帖子，我整理了一个教程，解释如何用c++ API加载TensorFlow图。它非常简单，应该帮助您理解所有的部分是如何组合在一起的。这是它的核心:

要求:

巴泽尔安装 克隆TensorFlow回购

文件夹结构:

tensorflow tensorflow / | | /项目名称 Tensorflow / Tensorflow /|项目名称|/|项目名称|。Cc(例如https://gist.github.com/jimfleming/4202e529042c401b17b7) tensorflow / tensorflow / | |项目名称/构建

构建:

cc_binary(
    name = "<project name>",
    srcs = ["<project name>.cc"],
    deps = [
        "//tensorflow/core:tensorflow",
    ]
)

有两点需要注意，但可能有变通办法:

现在，构建需要在TensorFlow回购中进行。 编译后的二进制文件很大(103MB)。

https://medium.com/@jimfleming/loading-a-tensorflow-graph-with-the-c-api-4caaff88463f

你可以使用这个ShellScript来安装(大多数)它的依赖，克隆，构建，编译和得到所有必要的文件到../ src /包括文件夹:

https://github.com/node-tensorflow/node-tensorflow/blob/master/tools/install.sh

Tensorflow本身只提供了关于c++ api的非常基本的示例。 这是一个很好的资源，包括数据集的例子，rnn, lstm, cnn等 Tensorflow c++的例子

如果你不想自己构建Tensorflow，而且你的操作系统是Debian或Ubuntu，你可以下载带有Tensorflow C/ c++库的预构建包。这个发行版可以用于CPU的C/ c++推理，GPU支持不包括在内:

https://github.com/kecsap/tensorflow_cpp_packaging/releases

这里有一些关于如何在Tensorflow (TFLearn)中冻结检查点的说明，并使用C/ c++ API加载这个模型进行推理:

https://github.com/kecsap/tensorflow_cpp_packaging/blob/master/README.md

注意:我是这个Github项目的开发者。