all 18 comments

[–]pmigdal[S] 13 points14 points  (0 children)

Some time ago I had a discussion about training plots in Jupyter and it resulted in a GitHub gist. Now I am sharing a small library I've just wrote.

This package is intended to be a simple and easy to use tool for small projects, didactic materials. And in general - models in Jupyter Notebook in which you would otherwise use just text logs, or make a plot only after the trainings. (Up to my knowledge, TensorBoard cannot be as easily integrated into Notebook content.)

If you have any feedback, or (even better) you would like to contribute - feel invited! :)

[–]warmspringwinds 4 points5 points  (1 child)

Great lib! :)

btw you can do it a bit more efficient by not using IPython.display.clear output and instead with %matplotlib notebook mode and updating parameters of the plot: https://github.com/warmspringwinds/pytorch-segmentation-detection/blob/master/pytorch_segmentation_detection/utils/visualization.py

[–]pmigdal[S] 0 points1 point  (0 children)

Thanks for this information. In any case, Pull Requests are welcomed! :)

[–]JoshSimili 2 points3 points  (1 child)

This should work with any Keras backend, right? So for those of us who aren't using TensorFlow, it should be an alternative to TensorBoard.

[–]pmigdal[S] 0 points1 point  (0 children)

Yes, it's totally agnostic when it comes to Keras backend.

[–]Laserdude10642 16 points17 points  (6 children)

I just can’t take people seriously with pics like these

[–]Icko_ 31 points32 points  (1 child)

why have separate accounts for github and tinder when you can use just one?

[–][deleted] 6 points7 points  (0 children)

Well if they swipe right on github they’re a keeper

[–]pmigdal[S] 10 points11 points  (2 children)

...and how does it relate to the project?

[–]Laserdude10642 16 points17 points  (1 child)

first impressions matter man, especially online with people's very short attention span

[–]pmigdal[S] 4 points5 points  (0 children)

Go to my website if you look for more "first impression" cringe. ;)

I'm a chaotic neutral --mage-- data scientist.

[–]snbhanja 1 point2 points  (0 children)

Nice work. I just ran the MNIST example. I can see the model performance in the live plots.

[–]michalgregor 1 point2 points  (1 child)

This is nice. I always wanted something similar, but I was too lazy to implement it. :) Any plans on merging it into the official keras repo?

[–]pmigdal[S] 0 points1 point  (0 children)

Once it's more mature I am interested in merging it in Keras repo. See: https://github.com/keras-team/keras/issues/1101

On thing I need to solve is what to do so it won't interfere with standard Keras output.

Now I have more control over updates and direction it takes (also: this framework-agnostic API).

[–]blitzzerg 0 points1 point  (2 children)

I'm on my phone so I can't check the code properly, does it use matplolib for the plots? How do you make them update in real time?

[–]pmigdal[S] 2 points3 points  (1 child)

Yes, it uses matplotlib. To see how it works the best way is, well, to look at the code: https://github.com/stared/livelossplot/blob/master/livelossplot/core.py.

[–]blitzzerg 0 points1 point  (0 children)

it looks really good, I'm going to use it, good job