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Tensorflow.js – A Practical Guide

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Re: Tensorflow.js – A Practical Guide

#22
post #21

Is there a TF/Keras in Python to JavaScript transpiler somewhere? I don't want to waste time retyping complex methods to JS. Thanks for any suggestion!

You can probably export your Keras model, load it in tensorflow.js, and train it. Makes more sense than transpiling.

Guide here:

https://js.tensorflow.org/tutorials/import-keras.html

Re: Tensorflow.js – A Practical Guide

#23
post #8

Earlier quoted context omitted.

Tensorflow tries to fit the free parameters (usually millions of parameters) of a function y=f(x). The fitting algorithm gets usually thousands or millions of examples of how the output y for a given input x has to look like. For example, x can be tens of thousands of images of cats and dogs, and y can be 1 for a dog and 0 for a cat. The goal for the fitting algorithm is to find parameters that describe the concept o…

If I understand it correctly: - Tensorflow is the best tool to make the grunt work necessary to calibrate the parameters of fitting algorithms. - Models of fitting algorithms are human proposed and where the ML 'art' is. Seems to be kind of reverse engineering.

Accurate, although in most cases, the art is not in choosing the algorithm (often a regular feed-forward, covolutional or recurrent neural network) but the hyperparameters (regularization, number of layers, units, etc.) and sometimes the way the data is fed (augment the dataset with distortions? sample negative examples randomly? etc.)

Re: Tensorflow.js – A Practical Guide

#24
post #14

Earlier quoted context omitted.

> So this is "we don't want to use another language". Yup, which is a perfectly valid reason. > If calling out to a binary is a security problem for you You miss the point. The security problem is sending the raw data from the client to the server. > So again, this boils down to "I don't want to use Python and I'd prefer to use JS instead." Which once again, is a perfectly valid reason > Servers are expensive so host…

"You miss the point. The security problem is sending the raw data from the client to the server." So don't do that. If you can run tensorflow on your device, you can call out to a local process. If you want to use JS to do everything, fine. But that's not a good reason. It's just a reason.

How can you run Python tensorflow locally? We're talking about web apps here.

Try to understand what is at play here. It's not all about raw performance, there are many more important things to consider that GP explained extensively.

Re: Tensorflow.js – A Practical Guide

#25
post #14

Earlier quoted context omitted.

> So this is "we don't want to use another language". Yup, which is a perfectly valid reason. > If calling out to a binary is a security problem for you You miss the point. The security problem is sending the raw data from the client to the server. > So again, this boils down to "I don't want to use Python and I'd prefer to use JS instead." Which once again, is a perfectly valid reason > Servers are expensive so host…

"You miss the point. The security problem is sending the raw data from the client to the server." So don't do that. If you can run tensorflow on your device, you can call out to a local process. If you want to use JS to do everything, fine. But that's not a good reason. It's just a reason.

> So don't do that. If you can run tensorflow on your device, you can call out to a local process.

Not from a webapp (without jumping through a dozen other hoops.) With tensorflow.js, you can do (for example) pose estimation, or face detection, or audio recognition, right in the browser without sending data to a remote server.

> But that's not a good reason. It's just a reason.

Yes, of course it's a reason. The point is that it can be a good reason in many cases.

Re: Tensorflow.js – A Practical Guide

#26
post #15
post #4

You were so busy figuring out if you could, you didn't stop to wonder if you should… Joking aside this is super cool

I was going to upvote you ‘til I read the last line

haha take my upvote sir. i'm looking forward to new breed of websites that abuse our browsers unknowingly. First mining crypto, now we will have people using thousands(millions) of web browsers as part of some elaborate compute cluster that runs some 'AI' deep learning crap to try and optimize branding/click rates etc.

Re: Tensorflow.js – A Practical Guide

#28
post #21

Is there a TF/Keras in Python to JavaScript transpiler somewhere? I don't want to waste time retyping complex methods to JS. Thanks for any suggestion!

You can probably export your Keras model, load it in tensorflow.js, and train it. Makes more sense than transpiling. Guide here: https://js.tensorflow.org/tutorials/import-keras.html

Thanks! Do you by chance know if it is practical to convert huge .h5 Keras models to TF.js layers model? (~1GB). I have some state-of-art computer vision models and it would be great if they could be used in a browser with a WebCam, if they can fit into memory and be performant for inferencing.

Re: Tensorflow.js – A Practical Guide

#29
post #14

Earlier quoted context omitted.

"You miss the point. The security problem is sending the raw data from the client to the server." So don't do that. If you can run tensorflow on your device, you can call out to a local process. If you want to use JS to do everything, fine. But that's not a good reason. It's just a reason.

How can you run Python tensorflow locally? We're talking about web apps here. Try to understand what is at play here. It's not all about raw performance, there are many more important things to consider that GP explained extensively.

[deleted]

Re: Tensorflow.js – A Practical Guide

#30
post #25
post #14

Earlier quoted context omitted.

"You miss the point. The security problem is sending the raw data from the client to the server." So don't do that. If you can run tensorflow on your device, you can call out to a local process. If you want to use JS to do everything, fine. But that's not a good reason. It's just a reason.

> So don't do that. If you can run tensorflow on your device, you can call out to a local process. Not from a webapp (without jumping through a dozen other hoops.) With tensorflow.js, you can do (for example) pose estimation, or face detection, or audio recognition, right in the browser without sending data to a remote server. > But that's not a good reason. It's just a reason. Yes, of course it's a reason. The point…

[deleted]
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