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TextGAN is a PyTorch framework for Generative Adversarial Networks (GANs) based text generation models.

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Bumps [numpy](https://github.com/numpy/numpy) from 1.14.5 to 1.22.0. Release notes Sourced from numpy's releases. v1.22.0 NumPy 1.22.0 Release Notes NumPy 1.22.0 is a big release featuring the work of 153 contributors spread...

dependencies

Hello there! We would like refer to your repository in an academic article. Right now we are citing the repository by URL, but if you would like a more specific...

How does seqgan train on real data?

I am running the codes on macOS without NVIDIA GPU Graphic Card available. I wonder how I can run the scripts in CPU-only mode. What sections should I modify? Thanks...

Thanks for your coding.I have some small problems,could you help me? When I use my dataset,it happens. `> training arguments: >>> if_test: False >>> run_model: seqgan >>> k_label: 2 >>>...

when i run run_seqgan.py 1 1,the CPU usage rate reaches 100% Please tell me how to solve this problem,thanks

> training arguments: >>> if_test: False >>> run_model: maligan >>> k_label: 2 >>> dataset: treasure-island >>> model_type: vanilla >>> loss_type: rsgan >>> mu_type: ragan >>> eval_type: Ra >>> d_type: Ra...

Hi @williamSYSU, Thanks for the work. I found a potential bug in your seqgan rollout code. In the below code snippet in function `get_reward` in utils/rollout.py, ```python rewards = torch.zeros([rollout_num...

I have tried the SentiGAN with the default parameters to reproduce the synthetic results reported in your paper CatGAN, but i failed. Could you please share the correct parameters you...

Is it convenient to describe the composition of your stock.csv data, I don't quite understand the Time output in your data_loading section.