Inspiration

pytorch have a great role in making GAN module. TESTGAN pytorch is a pytorch framework for GENERATIVE ADVERSARIAL NETWORK GAN* Textgan serve as a benchmarking platform to support research on GAN based text generation models. Since most GEN based text generation models are implemented by tensorflow, TESTGAN can help these who get use to pytorch to enter text generation field faster. Do it Inspired us to use great pytorch with other libraries such as num,ntlk to make GAN* MODULE with pytorch

What it does

Textgan pytorch help those who get used to pytorch to enter the text generation field faster as those who not use tensorflow.

How we built it

It's build with such libraries as following... .Python >=1.1.0 .Nump 1.14.5 .Python 3.6 .Cudq7.5+*For GPU .nltk 3.4 .tqdm 4.32.1 . Kenlm (https://github.com/kpu/kenlm)

Challenges we ran into

When we started to build we have problems to find out reasrch papers deal with great libraries suh as numpy cuda but we do that for pytorch users.

Accomplishments that we're proud of

We are proud that we worked with such great libraries numpy1.14.5, pytorch cuda and kenlm its was great experience and we learned alot..

What we learned

We learned different way and how to use such great libto make good use ful models liks TEXTGAN PYTORCH for pytorch, python influncers.

What's next for TEXTGAN PYTORCH

Its tha part of university project...

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