- #Swift mac os framework how to
- #Swift mac os framework install
- #Swift mac os framework full
- #Swift mac os framework license
This static framework can be used in the exact same way as theĭynamic one. Under bazel-bin/tensorflow/lite/ios/ directory under your TensorFlow rootĭirectory.
The command will generate a file named TensorFlowLiteC_static_framework.zip tensorflow/lite/ios:TensorFlowLiteC_static_framework To use the static framework instead, you can build the TensorFlowLiteC staticįramework with the following command: bazel build -config=ios_fat -c opt \ Build TensorFlowLiteC static frameworkīy default, we only distribute the dynamic framework via Cocoapods. You specify -config=ios_fat, please refer to the iOS configs section in the
#Swift mac os framework full
To see the full list of build flags used when This command will generate the TensorFlowLiteC_framework.zip file underīazel-bin/tensorflow/lite/ios/ directory under your TensorFlow root directory.īy default, the generated framework contains a "fat" binary, containing armv7,Īrm64, and x86_64 (but no i386). tensorflow/lite/ios:TensorFlowLiteC_framework TensorFlowLiteC framework with the following command. Once Bazel is properly configured with iOS support, you can build the In theseĬases, skip to the Use in your own application You only want to test local changes to the Swift or Objective-C APIs. Build TensorFlowLiteC dynamic framework (recommended) Note: This step is not necessary if (1) you are using Bazel for your app, or (2) configure script in the root TensorFlow checkout directory, andĪnswer "Yes" when the script asks if you wish to build TensorFlow with iOS Version between _TF_MIN_BAZEL_VERSION and _TF_MAX_BAZEL_VERSION inĬonfigure.py file at the root of tensorflow repository. Users with the following command: sudo xcodebuild -license acceptīazel is the primary build system for TensorFlow.
#Swift mac os framework license
If this is a new install, you will need to accept the license agreement for all Using xcode-select: xcode-select -install
#Swift mac os framework install
If you have not already, you will need to install Xcode 8 or later and the tools You need to build it using Bazel on a macOS machine. To create a universal iOS framework for TensorFlow Lite locally, In some cases, you might wish to use a local build of TensorFlow Lite, forĮxample when you want to make local changes to TensorFlow Lite and test thoseĬhanges in your iOS app or you prefer using static framework to our providedĭynamic one.
#Swift mac os framework how to
See iOS quickstart for moreĭetails on how to use them in your iOS projects. Releases of the TensorFlow Lite CocoaPods. Just want to use it, the easiest way is using the prebuilt stable or nightly Normally, you do not need to locally build TensorFlow Lite iOS library. As you can see there isn't too much to Module Stability.This document describes how to build TensorFlow Lite iOS library on your own. The format should be pretty familiar if you've looked at the generated interface of a Swift file, with the exception being the inclusion of the bodies of functions. Where in C/C++/ObjC, public methods are exposed via a handwritten header, Swift module stability will come from a pretty-straightforward generated equivalent. Module stability is basically just adding a Swift equivalent of a header in C. Currently there is an opaque binary "swiftmodule" that the compiler can read to determine available methods, but it's not consistently formatted from version to version.
The next step is "Module Stability", which introduces the ability for the compiler to know what methods are available between two Swift versions. Previously, if two binaries were compiled with two different Swift versions, it was not guaranteed that one could call into the other and get the expected result. Swift 5 introduces "ABI Stability", which means the calling conventions between two binaries is now guaranteed to be consistent.
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