Metadata-Version: 2.1
Name: tensorlayer
Version: 2.2.2
Summary: High Level Tensorflow Deep Learning Library for Researcher and Engineer.
Home-page: https://github.com/tensorlayer/tensorlayer
Author: TensorLayer Contributors
Author-email: tensorlayer@gmail.com
Maintainer: TensorLayer Contributors
Maintainer-email: tensorlayer@gmail.com
License: apache
Download-URL: https://github.com/tensorlayer/tensorlayer
Description: |TENSORLAYER-LOGO|
        
        
        |Awesome| |Documentation-EN| |Documentation-CN| |Book-CN| |Downloads|
        
        |PyPI| |PyPI-Prerelease| |Commits-Since| |Python| |TensorFlow|
        
        |Travis| |Docker| |RTD-EN| |RTD-CN| |PyUP| |Docker-Pulls| |Code-Quality|
        
        
        |JOIN-SLACK-LOGO|
        
        TensorLayer is a novel TensorFlow-based deep learning and reinforcement
        learning library designed for researchers and engineers. It provides a
        large collection of customizable neural layers / functions that are key
        to build real-world AI applications. TensorLayer is awarded the 2017
        Best Open Source Software by the `ACM Multimedia
        Society <http://www.acmmm.org/2017/mm-2017-awardees/>`__.
        
        Design Features
        =================
        
        TensorLayer is a new deep learning library designed with simplicity, flexibility and high-performance in mind.
        
        - **Simplicity** : TensorLayer has a high-level layer/model abstraction which is effortless to learn. You can learn how deep learning can benefit your AI tasks in minutes through the massive [examples](https://github.com/tensorlayer/awesome-tensorlayer).
        - **Flexibility** : TensorLayer APIs are transparent and flexible, inspired by the emerging PyTorch library. Compared to the Keras abstraction, TensorLayer makes it much easier to build and train complex AI models.
        - **Zero-cost Abstraction** : Though simple to use, TensorLayer does not require you to make any compromise in the performance of TensorFlow (Check the following benchmark section for more details).
        
        TensorLayer stands at a unique spot in the TensorFlow wrappers. Other wrappers like Keras and TFLearn
        hide many powerful features of TensorFlow and provide little support for writing custom AI models. Inspired by PyTorch, TensorLayer APIs are simple, flexible and Pythonic,
        making it easy to learn while being flexible enough to cope with complex AI tasks.
        TensorLayer has a fast-growing community. It has been used by researchers and engineers all over the world, including those from  Peking University,
        Imperial College London, UC Berkeley, Carnegie Mellon University, Stanford University, and companies like Google, Microsoft, Alibaba, Tencent, Xiaomi, and Bloomberg.
        
        Install
        =======
        
        TensorLayer has pre-requisites including TensorFlow, numpy, and others. For GPU support, CUDA and cuDNN are required.
        The simplest way to install TensorLayer is to use the Python Package Index (PyPI):
        
        .. code:: bash
        
            # for last stable version
            pip install --upgrade tensorlayer
        
            # for latest release candidate
            pip install --upgrade --pre tensorlayer
        
            # if you want to install the additional dependencies, you can also run
            pip install --upgrade tensorlayer[all]              # all additional dependencies
            pip install --upgrade tensorlayer[extra]            # only the `extra` dependencies
            pip install --upgrade tensorlayer[contrib_loggers]  # only the `contrib_loggers` dependencies
        
        Alternatively, you can install the latest or development version by directly pulling from github:
        
        .. code:: bash
        
            pip install https://github.com/tensorlayer/tensorlayer/archive/master.zip
            # or
            # pip install https://github.com/tensorlayer/tensorlayer/archive/<branch-name>.zip
        
        Using Docker - a ready-to-use environment
        -----------------------------------------
        
        The `TensorLayer
        containers <https://hub.docker.com/r/tensorlayer/tensorlayer/>`__ are
        built on top of the official `TensorFlow
        containers <https://hub.docker.com/r/tensorflow/tensorflow/>`__:
        
        Containers with CPU support
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        .. code:: bash
        
            # for CPU version and Python 2
            docker pull tensorlayer/tensorlayer:latest
            docker run -it --rm -p 8888:8888 -p 6006:6006 -e PASSWORD=JUPYTER_NB_PASSWORD tensorlayer/tensorlayer:latest
        
            # for CPU version and Python 3
            docker pull tensorlayer/tensorlayer:latest-py3
            docker run -it --rm -p 8888:8888 -p 6006:6006 -e PASSWORD=JUPYTER_NB_PASSWORD tensorlayer/tensorlayer:latest-py3
        
        Containers with GPU support
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        NVIDIA-Docker is required for these containers to work: `Project
        Link <https://github.com/NVIDIA/nvidia-docker>`__
        
        .. code:: bash
        
            # for GPU version and Python 2
            docker pull tensorlayer/tensorlayer:latest-gpu
            nvidia-docker run -it --rm -p 8888:88888 -p 6006:6006 -e PASSWORD=JUPYTER_NB_PASSWORD tensorlayer/tensorlayer:latest-gpu
        
            # for GPU version and Python 3
            docker pull tensorlayer/tensorlayer:latest-gpu-py3
            nvidia-docker run -it --rm -p 8888:8888 -p 6006:6006 -e PASSWORD=JUPYTER_NB_PASSWORD tensorlayer/tensorlayer:latest-gpu-py3
        
        Contribute
        ==========
        
        Please read the `Contributor
        Guideline <https://github.com/tensorlayer/tensorlayer/blob/master/CONTRIBUTING.md>`__
        before submitting your PRs.
        
        Cite
        ====
        
        If you find this project useful, we would be grateful if you cite the
        TensorLayer paper：
        
        ::
        
            @article{tensorlayer2017,
                author  = {Dong, Hao and Supratak, Akara and Mai, Luo and Liu, Fangde and Oehmichen, Axel and Yu, Simiao and Guo, Yike},
                journal = {ACM Multimedia},
                title   = {{TensorLayer: A Versatile Library for Efficient Deep Learning Development}},
                url     = {http://tensorlayer.org},
                year    = {2017}
            }
        
        License
        =======
        
        TensorLayer is released under the Apache 2.0 license.
        
        
        .. |TENSORLAYER-LOGO| image:: https://raw.githubusercontent.com/tensorlayer/tensorlayer/master/img/tl_transparent_logo.png
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        .. |Awesome| image:: https://awesome.re/mentioned-badge.svg
           :target: https://github.com/tensorlayer/awesome-tensorlayer
        .. |Documentation-EN| image:: https://img.shields.io/badge/documentation-english-blue.svg
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        .. |Book-CN| image:: https://img.shields.io/badge/book-%E4%B8%AD%E6%96%87-blue.svg
           :target: http://www.broadview.com.cn/book/5059/
        .. |Downloads| image:: http://pepy.tech/badge/tensorlayer
           :target: http://pepy.tech/project/tensorlayer
        
        
        .. |PyPI| image:: http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/github/release/tensorlayer/tensorlayer.svg?label=PyPI%20-%20Release
           :target: https://pypi.org/project/tensorlayer/
        .. |PyPI-Prerelease| image:: http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/github/release/tensorlayer/tensorlayer/all.svg?label=PyPI%20-%20Pre-Release
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        .. |Python| image:: http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/pypi/pyversions/tensorlayer.svg
           :target: https://pypi.org/project/tensorlayer/
        .. |TensorFlow| image:: https://img.shields.io/badge/tensorflow-1.6.0+-blue.svg
           :target: https://github.com/tensorflow/tensorflow/releases
        
        .. |Travis| image:: http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/travis/tensorlayer/tensorlayer/master.svg?label=Travis
           :target: https://travis-ci.org/tensorlayer/tensorlayer
        .. |Docker| image:: http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/circleci/project/github/tensorlayer/tensorlayer/master.svg?label=Docker%20Build
           :target: https://circleci.com/gh/tensorlayer/tensorlayer/tree/master
        .. |RTD-EN| image:: http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/readthedocs/tensorlayer/latest.svg?label=ReadTheDocs-EN
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        .. |RTD-CN| image:: http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/readthedocs/tensorlayercn/latest.svg?label=ReadTheDocs-CN
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        .. |PyUP| image:: https://pyup.io/repos/github/tensorlayer/tensorlayer/shield.svg
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        .. |Docker-Pulls| image:: http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/docker/pulls/tensorlayer/tensorlayer.svg
           :target: https://hub.docker.com/r/tensorlayer/tensorlayer/
        .. |Code-Quality| image:: https://api.codacy.com/project/badge/Grade/d6b118784e25435498e7310745adb848
           :target: https://www.codacy.com/app/tensorlayer/tensorlayer
        
Keywords: deep learning,machine learning,computer vision,nlp,supervised learning,unsupervised learning,reinforcement learning,tensorflow
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Information Technology
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Utilities
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Environment :: Console
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Provides-Extra: tf_cpu
Provides-Extra: tf_gpu
Provides-Extra: extra
Provides-Extra: contrib_loggers
Provides-Extra: test
Provides-Extra: dev
Provides-Extra: doc
Provides-Extra: db
Provides-Extra: all
Provides-Extra: all_cpu
Provides-Extra: all_gpu
Provides-Extra: all_dev
Provides-Extra: all_cpu_dev
Provides-Extra: all_gpu_dev
