TensorFlow博客翻譯——TensorFlow v0.9發布，帶有增強版的移動支持

TensorFlow v0.9 now available with improved mobile support

Posted by Pete Warden, Software Engineer

When we started building TensorFlow, supporting mobile devices was a top priority. We were already supporting many of Google』s mobile apps like Translate, Maps, and the Google app, which use neural networks running on devices. We knew that we had to make mobile a first-class part of open source TensorFlow.

當我們開始構建TensorFlow的時候，支持移動設備是一個首要選項。我們已經支持了很多Google移動Apps,比如：翻譯，地圖和使用神經網路並運行在設備上的Google應用。我們知道我們必須讓移動支持成為開源的TensorFlow的第一流的部件。

TensorFlow has been available to developers on Android since launch, and today were happy to add iOS in v0.9 of TensorFlow, along with Raspberry Pi support and new compilation options.

從一開始，TensorFlow就可以支持Android開發，現在我們非常高興的把對iOS的支持添加到TensorFlow的v0.9版本中，與此同時，我們還支持了樹莓派和一些新的編譯選項。

To build TensorFlow on iOS we』ve created a set of scripts, including a makefile, to drive the cross-compilation process. The makefile can also help you build TensorFlow without using Bazel, which is not always available.

為了在iOS上構建TensorFlow，我們創建了一些列的腳本，包括一個驅動交叉編譯進程的makefile。這個makefile也可以幫助你在不使用Bazel的情況下構建TensorFlow，因為Bazel經常不太好用。

All this is in the latest TensorFlow distribution. You can read more by visiting our Mobile TensorFlow guide and the documentation in our iOS samples and Android sample. The mobile samples allow you to classify images using the ImageNet Inception v1 classifier.

所有的這些特徵都已經在最新的TensorFlow發布版里了。你可以通過訪問我們的Mobile TensorFlow guide和我們iOS samples 和 Android sample的文檔獲取更多的信息。這些移動端的例子允許你使用ImageNet Inception v1 classifier去歸類圖片。

These mobile samples are just the beginning---wed love your help and your contributions. Tag social media posts with #tensorflow so we can hear about your projects!

這些移動端的例子只是開始，我們歡迎你的幫助和你的貢獻。請在社交媒體的發布上打上#tensorflow的標記，這樣我們可以接收到你的項目。

See the full TensorFlow 0.9.0 release notes here.

查看TensorFlow 0.9.0的完成版發布通告請點這裡。

本博客是原創翻譯，如果轉載請提前獲得本人同意。