TensorFlow C API Examples

TensorFlow C API examples for Windows, Linux, and macOS, with a small C++ helper library.

Requirements

• CMake 3.20 or newer and a C++17 compiler.
• Python with pip; CI uses Python 3.12.
• A 64-bit platform supported by the TensorFlow wheel.

Build and test

git clone --depth 1 https://github.com/Neargye/hello_tf_c_api
cd hello_tf_c_api

Windows (Visual Studio)

cmake -S . -B build -A x64
cmake --build build --config Release
ctest --test-dir build --output-on-failure -C Release

Linux and macOS

cmake -S . -B build -DCMAKE_BUILD_TYPE=Release
cmake --build build
ctest --test-dir build --output-on-failure

CMake downloads the TensorFlow 2.21.0 wheel into build/_deps/tensorflow/python and links its native libraries. On Windows, it also copies the runtime DLLs. You do not need to install TensorFlow into your Python environment to build the C++ examples.

The repository includes models/graph.pb. Run examples from the build directory so they can find its copy: ./Release/repeated_inference.exe on Windows or ./repeated_inference on Linux/macOS.

Build options

Pass these options to cmake -S . -B build:

• -DHELLO_TF_BUILD_EXAMPLES=OFF: skip example executables.
• -DBUILD_TESTING=OFF: skip tests.
• -DTENSORFLOW_ROOT=/path/to/tensorflow -DHELLO_TF_FETCH_TENSORFLOW=OFF: use an existing wheel extraction. Headers must be under <root>/python/tensorflow/include, with native libraries under <root>/python/tensorflow or its python subdirectory. CMake does not overwrite an external root.

OpenCV is optional. CMake builds and tests the OpenCV example when it finds the library.

Examples

• TensorFlow version, load a graph.
• Create a tensor, allocate a tensor, string tensors.
• Run a session, run a target operation.
• Helper API, batch inference, repeated inference.
• Image tensors, image files with OpenCV.
• Tensor information, graph information.

Helper API

See tf_utils.hpp for declarations. Within this CMake project, link the helpers with:

target_link_libraries(your_target PRIVATE hello_tf_utils)

For raw C API examples, use the project's target_link_tensorflow(your_target) function. There is no installable CMake package.

• CreateTensor(dims, values) infers the TensorFlow type from the vector element type. Use CreateStringTensor for strings.
• Reader overloads taking a result reference return TF_Code and leave the result unchanged on error. They distinguish errors from valid empty values.
• The checked GetTensorShape writes nullopt for unknown rank, an empty vector for a scalar, and -1 for unknown dimensions.
• RunSession requires output slots initialized to nullptr. Delete returned tensors and reset the slots before reuse.

More

• Prepare models: GraphDef, operation names, and checkpoints.
• Runtime and performance: resource reuse and measurement.
• Create a Windows import library: only for manual linking.

Licensed under the MIT License