hello_tf_c_api

Introduction to the Hello TF C API Project

The Hello TF C API project serves as a comprehensive example demonstrating how to effectively utilize the TensorFlow C API across various operating systems, including Windows, Linux, and macOS. This initiative is invaluable for developers interested in leveraging TensorFlow's capabilities in C/C++ environments, providing practical insights and examples on performing fundamental operations with TensorFlow.

Example Demonstrations

The project includes several practical examples to guide users through different aspects of using the TensorFlow C API:

• Hello TF: Introduces users to the basics of integrating TensorFlow with C++. View the Example
• Load Graph: Demonstrates loading a pre-trained TensorFlow graph. View the Example
• Create Tensor: Guides users on creating tensors within the C API framework. View the Example
• Allocate Tensor: Shows how to allocate memory for tensors. View the Example
• Run Session: Explains how to run a TensorFlow session using the C API. View the Example
• Interface: Details setting up interfaces for interacting with TensorFlow. View the Example
• Tensor Info and Graph Info: Provides methods for obtaining information about tensors and graphs respectively. Tensor Info Example, Graph Info Example
• Image Processing: An advanced example of applying TensorFlow to image processing tasks. View the Example

Building the Examples

The project supports building examples across different operating systems with easy-to-follow steps.

Windows

To set up on Windows:

git clone --depth 1 https://github.com/Neargye/hello_tf_c_api
cd hello_tf_c_api
mkdir build
cd build
cmake -G "Visual Studio 15 2017" -A x64 ..
cmake --build . --config Debug

Linux

For Linux systems:

git clone --depth 1 https://github.com/Neargye/hello_tf_c_api
cd hello_tf_c_api
mkdir build
cd build
cmake -G "Unix Makefiles" ..
cmake --build .

macOS (Darwin)

For users on macOS:

git clone --depth 1 https://github.com/Neargye/hello_tf_c_api
cd hello_tf_c_api
mkdir build
cd build
cmake -G "XCode" ..
cmake --build .

Important Notes

• Post-build, the TensorFlow library and headers are located in the hello_tf_c_api/tensorflow/lib and hello_tf_c_api/tensorflow/include directories, respectively.
• Ensure that the project targets 64-bit platforms, as the TensorFlow in the repository is compiled in x64 mode.
• The TensorFlow library should either be in the output directory or within a directory specified by the %PATH% environment variable.

Obtaining and Linking the TensorFlow Library

Users can obtain prebuilt TensorFlow binaries for x64 CPUs from the official TensorFlow website or compile them with desired CPU/GPU support.

To link the TensorFlow library in a project:

Using CMakeLists.txt

Include the following in your CMakeLists.txt:

link_directories(yourpath/to/tensorflow) # specify the path
target_link_libraries(<target> <PRIVATE|PUBLIC|INTERFACE> tensorflow)

Using Visual Studio

Include the path to your TensorFlow library in the project's properties under "Linker" --> "Additional Dependencies".

Additional Resources

For more information on preparing models and creating TensorFlow library files on Windows, refer to the documentation and the detailed guide.

Licensing

The Hello TF C API project is licensed under the MIT License, enabling open and flexible use of the code provided.