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How HBO’s Silicon Valley Built “Not Hotdog” with TensorFlow, Keras and React Native

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Re: How HBO’s Silicon Valley Built “Not Hotdog” with TensorFlow, Keras and React Native

#41

Post by [deleted] »

metakermit wrote: post #37
timanglade wrote: post #7

Earlier quoted context omitted.

One of my primary motivators behind building this blogpost was to show how exactly one can use TensorFlow to ship a production mobile application. There’s certainly a lot of material out there, but a lot of it is either light on details, or only fit for prototypes/demos. There was quite a bit of work involved in making TensorFlow work well on a variety of devices, and I’m proud we managed to get it down to just 50MB…

yeah, that's my main pain with the TF docs – great if you just want to try one of the MNIST tutorial variations, but there's a lot more you need to figure out when you get beyond of these "hello world" examples…

[deleted]

Re: How HBO’s Silicon Valley Built “Not Hotdog” with TensorFlow, Keras and React Native

#43

Post by timanglade »

mamon wrote: post #40
timanglade wrote: post #8

Just wanted to say thanks for the warm welcome from HN when the app was released last month — I hope this blogpost answers the questions that were raised back then. I’d be happy to answer anything else you’d like to know! Original thread: https://news.ycombinator.com/item?id=14347211 Demo of the app (in the show): https://www.youtube.com/watch?v=ACmydtFDTGs App for iOS: https://itunes.apple.com/app/not-hotdog/id12124…

Slightly offtopic, but I wonder how hard it was to attach eGPU to MacBook Pro? Is there some official support, or was it just a dirty hack?

Not offtopic at all! Dirty hack for sure. The enclosure I bought was a hack, the drivers were a hack, and there was software on top that was a hack as well. But the developer experience was totally awesome… Almost made the constant graphics crashes worth it. Almost.

Re: How HBO’s Silicon Valley Built “Not Hotdog” with TensorFlow, Keras and React Native

#48

Post by lightbyte »

timanglade wrote: post #36
lightbyte wrote: post #34

Earlier quoted context omitted.

Quick followup, what type of optimizer did you guys end up using?

SGD with Cyclical Learning Rates [0]. Honestly, it’s the closest to a Machine Learning silver bullet I’ve found to date! That paper is awesome . [0]: https://arxiv.org/abs/1506.01186

Thanks! I'm trying out your model on a small data set I've been playing with for identifying invasive species of flowers [0] and so far it's working way better than my initial version that was based on resnet (though slower)!

[0] https://www.kaggle.com/c/invasive-species-monitoring

Re: How HBO’s Silicon Valley Built “Not Hotdog” with TensorFlow, Keras and React Native

#49

Post by timanglade »

bigfish24 wrote: post #45

What kind of accuracy did you get with the transfer learning attempts?

Well for a while I was lulled into complacency because the retrained networks would indicate 98%+ accuracy, but really that was just an artifact of my 49:1 nothotdog:hotdog image imbalance. When I started weighing proportionately, a lot of networks were measurably lower, although it’s obviously possible to get Inception of Vgg back to a “true” 98% accuracy given enough training time.

That would have beat what I ended up shipping, but the problem of course was the size of those networks. So really, if we’re comparing apples to apples, I’ll say none of the “small”, mobile-friendly neural nets (e.g. SqueezeNet, MobileNet) I tried to retrain did anywhere near as well as my DeepDog network trained from scratch. The training runs were really erratic and never really reached any sort of upper bound asymptotically as they should. I think this has to do with the fact that these very small networks contain data about a lot of ImageNet classes, and it’s very hard to tune what they should retain vs. what they should forget, so picking your learning rate (and possibly adjusting it on the fly) ends up being very critical. It’s like doing neurosurgery on a mouse vs. a human I guess — the brain is much smaller, but the blade says the same size :-/

Re: How HBO’s Silicon Valley Built “Not Hotdog” with TensorFlow, Keras and React Native

#50

Post by timanglade »

cedric wrote: post #46

Interesting. What is the external GPU (eGPU) enclosure you used for the Nvidia GTX 980 Ti card? Is it this one? https://bizon-tech.com/us/bizonbox2s-egpu.html/

Yes, that’s what you see in the picture, although as completely personal advice, I would stop short of recommending it. For one there are arguably better cases out there now, and you can sometimes build your own eGPU rig for less. Finally, the Mac software integration (with any eGPU) is very hacky at the moment despite the community’s best efforts, and I had to deal with a lot of kernel panics and graphics crashes, so overall I’m not sure I would recommend others attempt the same setup.
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