Metadata-Version: 2.1
Name: rslib
Version: 1.1.0
Summary: offline train framework in diting group
Home-page: https://gitlab.leihuo.netease.com/userpersona/diting/rslib
Author: wangkai02
Author-email: wangkai02@corp.netease.com
License: MIT
Description: <div align="center">
          <img src="https://tva1.sinaimg.cn/large/006y8mN6ly1g7173kbi84j306602odg9.jpg
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        | **`Documentation`** |
        |-----------------|
        | [![Documentation](https://img.shields.io/badge/api-reference-blue.svg)](https://www.tensorflow.org/api_docs/) |
        谛听组推荐系统离线训练框架
        
        [TensorFlow](https://www.tensorflow.org/) is an end-to-end open source platform
        for machine learning. It has a comprehensive, flexible ecosystem of
        [tools](https://www.tensorflow.org/resources/tools),
        [libraries](https://www.tensorflow.org/resources/libraries-extensions), and
        [community](https://www.tensorflow.org/community) resources that lets
        researchers push the state-of-the-art in ML and developers easily build and
        deploy ML powered applications.
        
        TensorFlow was originally developed by researchers and engineers working on the
        Google Brain team within Google's Machine Intelligence Research organization for
        the purposes of conducting machine learning and deep neural networks research.
        The system is general enough to be applicable in a wide variety of other
        domains, as well.
        
        TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)
        and [C++](https://www.tensorflow.org/api_docs/cc) APIs, as well as
        non-guaranteed backwards compatible API for
        [other languages](https://www.tensorflow.org/api_docs).
        
        Keep up-to-date with release announcements and security updates by subscribing
        to
        [announce@tensorflow.org](https://groups.google.com/a/tensorflow.org/forum/#!forum/announce).
        See all the [mailing lists](https://www.tensorflow.org/community/forums).
        
        ## Install
        
        See the [TensorFlow install guide](https://www.tensorflow.org/install) for the
        [pip package](https://www.tensorflow.org/install/pip), to
        [enable GPU support](https://www.tensorflow.org/install/gpu), use a
        [Docker container](https://www.tensorflow.org/install/docker), and
        [build from source](https://www.tensorflow.org/install/source).
        
        To install the current release for CPU-only:
        
        ```
        $ pip install tensorflow
        ```
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