STT-tensorflow/tensorflow/lite/c/README.md
Karim Nosir dd02edce8b Update build commands
Tested:
bazel build -c opt --fat_apk_cpu=x86,x86_64,arm64-v8a,armeabi-v7a //tensorflow/lite/java:tensorflow-lite

With NDK r17c

PiperOrigin-RevId: 295248025
Change-Id: Ice7895ffb5ef53f5885532fdf66ae6ee9d012892
2020-02-14 16:14:14 -08:00

2.0 KiB

TensorFlow Lite C API

This directory contains C APIs for TensorFlow Lite. This includes C APIs for common types, like kernels and delegates, as well as an explicit C API for inference.

Header summary

Each public C header contains types and methods for specific uses:

  • common.h - Contains common C enums, types and methods used throughout TensorFlow Lite. This includes everything from error codes, to the kernel and delegate APIs.
  • builtin_op_data.h - Contains op-specific data that is used for builtin kernels. This should only be used when (re)implementing a builtin operator.
  • c_api.h - Contains the TensorFlow Lite C API for inference. The functionality here is largely equivalent (though a strict subset of) the functionality provided by the C++ Interpreter API.
  • c_api_experimental.h - Contains experimental C API methods for inference. These methods are useful and usable, but aren't yet part of the stable API.

Using the C API

See the c_api.h header for API usage details.

Building the C API

A native shared library target that contains the C API for inference has been provided. Assuming a working bazel configuration, this can be built as follows:

bazel build -c opt //tensorflow/lite/c:tensorflowlite_c

and for Android (replace android_arm with android_arm64 for 64-bit), assuming you've configured your project for Android builds:

bazel build -c opt --cxxopt=--std=c++11 --config=android_arm \
  //tensorflow/lite/c:tensorflowlite_c

The generated shared library will be available in your bazel-bin/tensorflow/lite/c directory. A target which packages the shared library together with the necessary headers (c_api.h, c_api_experimental.h and common.h) will be available soon, and will also be released as a prebuilt archive (together with existing prebuilt packages for Android/iOS).