Metadata-Version: 2.1
Name: tensorlayer
Version: 2.0.2
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/>`__.
        
        Why another deep learning library: TensorLayer
        ==============================================
        
        As deep learning practitioners, we have been looking for a library that
        can address various development purposes. This library is easy to adopt
        by providing diverse examples, tutorials and pre-trained models. Also,
        it allow users to easily fine-tune TensorFlow; while being suitable for
        production deployment. TensorLayer aims to satisfy all these purposes.
        It has three key features:
        
        -  **Simplicity** : TensorLayer lifts the low-level dataflow interface
           of TensorFlow to *high-level* layers / models. It is very easy to
           learn through the rich `example
           codes <https://github.com/tensorlayer/awesome-tensorlayer>`__
           contributed by a wide community.
        -  **Flexibility** : TensorLayer APIs are transparent: it does not
           mask TensorFlow from users; but leaving massive hooks that help
           *low-level tuning* and *deep customization*.
        -  **Zero-cost Abstraction** : TensorLayer can achieve the *full
           power* of TensorFlow. The following table shows the training speeds
           of classic models using TensorLayer and native TensorFlow on a Titan
           X Pascal GPU.
        
           +---------------+-----------------+-----------------+-----------------+
           |               | CIFAR-10        | PTB LSTM        | Word2Vec        |
           +===============+=================+=================+=================+
           | TensorLayer   | 2528 images/s   | 18063 words/s   | 58167 words/s   |
           +---------------+-----------------+-----------------+-----------------+
           | TensorFlow    | 2530 images/s   | 18075 words/s   | 58181 words/s   |
           +---------------+-----------------+-----------------+-----------------+
        
        TensorLayer stands at a unique spot in the library landscape. Other
        wrapper libraries like Keras and TFLearn also provide high-level
        abstractions. They, however, often hide the underlying engine from
        users, which make them hard to customize and fine-tune. On the contrary,
        TensorLayer APIs are generally flexible and transparent. Users often
        find it easy to start with the examples and tutorials, and then dive
        into TensorFlow seamlessly. In addition, TensorLayer does not create
        library lock-in through native supports for importing components from
        Keras, TFSlim and TFLearn.
        
        TensorLayer has a fast growing usage among top researchers and
        engineers, from universities like Imperial College London, UC Berkeley,
        Carnegie Mellon University, Stanford University, and University of
        Technology of Compiegne (UTC), 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
           :target: https://tensorlayer.readthedocs.io/
        .. |JOIN-SLACK-LOGO| image:: https://raw.githubusercontent.com/tensorlayer/tensorlayer/master/img/join_slack.png
           :target: https://join.slack.com/t/tensorlayer/shared_invite/enQtMjUyMjczMzU2Njg4LWI0MWU0MDFkOWY2YjQ4YjVhMzI5M2VlZmE4YTNhNGY1NjZhMzUwMmQ2MTc0YWRjMjQzMjdjMTg2MWQ2ZWJhYzc
        
        .. |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
           :target: https://tensorlayer.readthedocs.io/
        .. |Documentation-CN| image:: https://img.shields.io/badge/documentation-%E4%B8%AD%E6%96%87-blue.svg
           :target: https://tensorlayercn.readthedocs.io/
        .. |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
           :target: https://pypi.org/project/tensorlayer/
        .. |Commits-Since| image:: http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/github/commits-since/tensorlayer/tensorlayer/latest.svg
           :target: https://github.com/tensorlayer/tensorlayer/compare/1.10.1...master
        .. |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
           :target: https://tensorlayer.readthedocs.io/
        .. |RTD-CN| image:: http://ec2-35-178-47-120.eu-west-2.compute.amazonaws.com/readthedocs/tensorlayercn/latest.svg?label=ReadTheDocs-CN
           :target: https://tensorlayercn.readthedocs.io/
        .. |PyUP| image:: https://pyup.io/repos/github/tensorlayer/tensorlayer/shield.svg
           :target: https://pyup.io/repos/github/tensorlayer/tensorlayer/
        .. |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: all
Provides-Extra: doc
Provides-Extra: test
Provides-Extra: contrib_loggers
Provides-Extra: dev
Provides-Extra: extra
Provides-Extra: tf_cpu
Provides-Extra: all_dev
Provides-Extra: all_cpu_dev
Provides-Extra: all_gpu_dev
Provides-Extra: all_gpu
Provides-Extra: tf_gpu
Provides-Extra: db
Provides-Extra: all_cpu
