This repository implements Sequence Generative Adversarial Nets with Policy Gradient, applying GANs to discrete token sequence generation. The generator uses policy gradient where the discriminator provides reward signals passed back via Monte Carlo search. The code includes a two-stage training process: supervised pre-training with maximum likelihood estimation, followed by adversarial training to improve the generator.