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Developer preview of TensorFlow Lite

developers.googleblog.com

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Re: Developer preview of TensorFlow Lite

#61

Post by d4l3k »

pjmlp wrote: post #53

So it uses Bazel on Android.... Google devs, could you please get yourself together in one room and agree in ONE BUILD SYSTEM for Android?!? Gradle stable, cmake, ndk-build, Gradle unstable plugin, GN, Bazel, ..., whatever someone else does with their 20%. I keep collecting build systems just to build Gooogle stuff for Android.

It might be a tad annoying, but the rest of Tensorflow uses Bazel so it makes sense that Tensorflow Lite also uses it. It also probably matches the internal Google workflow better since Google uses Blaze internally.

Re: Developer preview of TensorFlow Lite

#63

Post by pjmlp »

d4l3k wrote: post #61
pjmlp wrote: post #53

So it uses Bazel on Android.... Google devs, could you please get yourself together in one room and agree in ONE BUILD SYSTEM for Android?!? Gradle stable, cmake, ndk-build, Gradle unstable plugin, GN, Bazel, ..., whatever someone else does with their 20%. I keep collecting build systems just to build Gooogle stuff for Android.

It might be a tad annoying, but the rest of Tensorflow uses Bazel so it makes sense that Tensorflow Lite also uses it. It also probably matches the internal Google workflow better since Google uses Blaze internally.

I thought it was to be used outside Google, not that we have to learn every single build system they happen to use inside.

Re: Developer preview of TensorFlow Lite

#65

Post by linuxkerneldev »

rajatmonga wrote: post #51
linuxkerneldev wrote: post #31

Earlier quoted context omitted.

> Looking forward to your feedback as you try it out. Thanks Rajat. We use typical Cortex-A9/A7 SoCs running plain Linux rather than Android. We would use it for inference. 1. Platform choice Why make TFL Android/iOS only? TF works on plain Linux. TFL even uses NDK and it would appear the inference part could work on plain Linux. 2. Performance I did not find any info on performance of TensorFlow Lite. Mainly interes…

1. The code is standard C/C++ with minimal dependencies so it should be buildable on even non-standard platforms. Linux is easy. 2. The interpreter is more optimized for being low overhead and the kernels are better optimized especially for ARM CPUs currently. While model performance varies by model - we have seen significant improvements on most models going from TensorFlow to TensorFlow Lite. We'll share benchmarks…

> The code is standard C/C++ with minimal dependencies so it should be buildable on even non-standard platforms. Linux is easy.

Glad to hear that Rajat. Since it is easy as you say, I look forward to your upcoming release with Linux as standard. :-)

Re: Developer preview of TensorFlow Lite

#66

Post by solipsism »

pjmlp wrote: post #63
d4l3k wrote: post #61

Earlier quoted context omitted.

It might be a tad annoying, but the rest of Tensorflow uses Bazel so it makes sense that Tensorflow Lite also uses it. It also probably matches the internal Google workflow better since Google uses Blaze internally.

I thought it was to be used outside Google, not that we have to learn every single build system they happen to use inside.

If all Google teams who make use of external build systems were going to agree on one (not likely), it would be Bazel.

Re: Developer preview of TensorFlow Lite

#67

Post by sarasuec »

azinman2 wrote: post #36
rajatmonga wrote: post #2

TensorFlow Lite is TensorFlow’s lightweight solution for mobile and embedded devices! TensorFlow has always run on many platforms, from racks of servers to tiny devices, but as the adoption of machine learning models has grown over the last few years, so has the need to deploy them on mobile and embedded devices. TensorFlow Lite enables low-latency inference of on-device machine learning models. Looking forward to yo…

Will CoreML (or any hardware acceleration) on iOS be supported?

We want to provide a great experience across all our supported platforms, and are exploring ways to provide a simpler experience with good acceleration on iOS as well.

Re: Developer preview of TensorFlow Lite

#68

Post by rajatmonga »

sandGorgon wrote: post #52
rajatmonga wrote: post #2

TensorFlow Lite is TensorFlow’s lightweight solution for mobile and embedded devices! TensorFlow has always run on many platforms, from racks of servers to tiny devices, but as the adoption of machine learning models has grown over the last few years, so has the need to deploy them on mobile and embedded devices. TensorFlow Lite enables low-latency inference of on-device machine learning models. Looking forward to yo…

Hi, I have written about this before ( https://news.ycombinator.com/item?id=15595689 ) , but are there serialization fixes between cloud training and mobile ? We have had huge issues in trying to figure out how to save models (freeze graph,etc) and load it on Android. If you look at my previous thread - it also mentions bugs,threads and support requests where people are consistently confused.

Agree, that is a big problem that we are working hard to solve. It isn't solved in this release, but it is high up on our task list.

Re: Developer preview of TensorFlow Lite

#70

Post by dangjc »

rajatmonga wrote: post #2

TensorFlow Lite is TensorFlow’s lightweight solution for mobile and embedded devices! TensorFlow has always run on many platforms, from racks of servers to tiny devices, but as the adoption of machine learning models has grown over the last few years, so has the need to deploy them on mobile and embedded devices. TensorFlow Lite enables low-latency inference of on-device machine learning models. Looking forward to yo…

Is it lite enough to compile with Emscripten and use via WebAssembly?
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