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    "info": {
        "author": "Qingyang Wu",
        "author_email": "wilwu@ucdavis.edu",
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            "License :: OSI Approved :: MIT License",
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        "description": "# TorchFly\n\nTorchFly is a PyTorch Fast Development Kit. The purpose is to learn the pipelines of the SOTA algorithms in Deep Learning areas like CV, NLP and RL. The utilities provided in this kit will shorten the time needed to rebuild some basic functions. Now, the kit is mainly for personal use, but will be updated from time to time. \n\n## Installation\n\n### Installing via pip:\nInstalling is simple using `pip`.\n\n   ```bash\n   pip install torchfly\n   ```\n   \n### Installing from source\nYou can clone the repository.\n    ```bash\n    git clone https://github.com/qywu/TorchFly.git\n    ```\n\n### Docker\nIt is recommended to run on Nvidia Docker for better performance.\n\n    ```bash\n    FROM nvcr.io/nvidia/pytorch:18.12.1-py3\n    RUN apt-get update\n    \n    RUN pip install torchfly\n    ```\n \n ## TODOS\n \n1. Custom Bucket Sampler\n\n2. Custom Beam Search\n\n \n ## Code References\n \n [FastAI](https://github.com/fastai)\n \n [AllenNLP](https://github.com/allenai/allennlp/)\n \n [Pytorch BERT](https://github.com/huggingface/pytorch-pretrained-BERT)",
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