anshuman23

Tensorflex: Tensorflow bindings for Elixir

Hello all,

I have been working on my proposed project called Tensorflex as part of Google Summer of Code 2018.. Tensorflex can be used for making predictions from input data on pre-trained Tensorflow models. Training as of now is only supported in the Python API (also C++ at a low-level) but Tensorflex fully supports Inference and can be used for making predictions. Moreover, Tensorflex is being worked on and improved everyday so if there are any particular features anyone has in mind, please feel free to get in touch with me!

As an introduction to using Tensorflex for making predictions from saved models, I have written a blog post: http://www.anshumanc.ml/gsoc/2018/06/14/gsoc/

To follow development, make sure to watch the Github repository here: GitHub - anshuman23/tensorflex: Tensorflow bindings for the Elixir programming language 💪 · GitHub

Cheers!

15 comments

#library #machine-learning #data-science #tensorflow

34 7511 15

2018-09-29 19:49:56 UTC

First Post!

juhalehtonen

Great! I was really excited to see this on the Google Summer of Code list of projects, glad to see it come to fruition You mentioned that training via Tensorflex is not supported yet. Do you have any timeline in mind for this feature to land?

Post #1

Most Liked

anshuman23

Hello Juha! Thanks for the vote of confidence

So any bindings for Tensorflow can only be written around the C API, which is publicly exposed by Google. Unfortunately, they have not added Training functionality to the C API yet. So we will have to wait and see when they do that and then we can support it in Tensorflex too. Also, most other Tensorflow bindings, such as the ones officially written for Golang, only support Inference.

Post #2

anshuman23

Hello!
@mat_garland_1 and others who might be interested, here is the link for the PR which showcases how to use an RNN-LSTM model for sentiment analysis in Tensorflex. I am going to be working on documentation and a blog post for this as well as the Inception model over the next week, but the description for this PR is sufficiently detailed to get a general idea in the meanwhile:
https://github.com/anshuman23/tensorflex/pull/25

Post #14

leifericf

Thank you for creating this library, @anshuman23.

I recently changed my position at work from business developer to data scientist and I’m in the process of digging into a bunch of tools for data wrangling and machine learning.

Python is one of the most common programming languages for data science, due to extensive and robust libraries, such as pandas, NumPy, scikit-learn, TensorFlow, Keras and TensorForce. Those are the primary tools that we use at my workplace at the moment.

I’ll be looking into using Tensorflex as an alternative for deploying machine learning models.

One thing I’m curious about: When you created Tensorflex, did you envision for it to become to Elixir sort of what Keras is to Python? That is, not just for model-serving, but also for training artificial neural networks, etc.—A more generic abstraction layer on top of TensorFlow, CNTK and Theano.

Elixir with it’s highly concurrent capabilities, focus on data transformation (e.g. data pipelines) and strong support for meta-programming, lends itself very well to data science and machine learning. It makes me very excited to see that other people have similar thoughts.

There is an incredible amount of potential for Elixir within data science and machine learning.

Post #15