CoT
(Beta Version!) Experiment Code for Paper ``CoT: Cooperative Training for Generative Modeling of Discrete Data''
Install / Use
/learn @desire2020/CoTREADME
Cooperative Training
Experiment Code for Paper ``CoT: Cooperative Training for Generative Modeling of Discrete Data''

Requirements
- Python 3.x
- tensorflow >= 1.6.0 (Make sure your CuDNN version matches tensorflow version! Otherwise CuDNNLSTM may not work properly!)
Introduction
We propose a new paradigm of algorithm for training tractable explicit density generative models like RNN language models.
The research paper CoT: Cooperative Training for Generative Modeling of Discrete Data is now available on arXiv and has been accepted by ICML 2019 as a conference paper.
Usage
We reproduce example codes to repeat the synthetic Turing test experiment with evaluations of NLL<sub>test</sub>, NLL<sub>oracle</sub>, balanced NLL and JSD(P || G) by the oracle model.
$ python3 cot.py
Start Cooperative Training...
batch: 0 nll_oracle 11.429975
batch: 0 nll_test 8.524782
cooptrain epoch# 0 jsd 8.365606
batch: 100 nll_oracle 10.475937
batch: 100 nll_test 7.9382834
cooptrain epoch# 1 jsd 7.330582
batch: 200 nll_oracle 10.38681
batch: 200 nll_test 7.868909
... ...
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