Metadata-Version: 2.1
Name: tensorlayerx
Version: 0.5.4
Summary: High Level Tensorflow Deep Learning Library for Researcher and Engineer.
Home-page: https://github.com/tensorlayer/TensorLayerX
Author: TensorLayer Contributors
Author-email: tensorlayerx@gmail.com
Maintainer: TensorLayer Contributors
Maintainer-email: tensorlayerx@gmail.com
License: apache
Download-URL: https://github.com/tensorlayer/TensorLayerX
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: extra
Provides-Extra: contrib_loggers
Provides-Extra: test
Provides-Extra: dev
Provides-Extra: doc
Provides-Extra: db
Provides-Extra: all
Provides-Extra: all_dev
License-File: LICENSE.rst

|TENSORLAYER-LOGO|



TensorLayerX is a deep learning library designed for researchers and engineers that is compatible with multiple deep learning frameworks such as TensorFlow,

MindSpore and PaddlePaddle, allowing users to run the code on different hardware like Nvidia-GPU and Huawei-Ascend.

It provides popular DL and RL modules that can be easily customized and assembled for tackling real-world machine learning problems.

More details can be found here. TensorLayerX will support TensorFlow, MindSpore, PaddlePaddle, and PyTorch backends in the future.



Install

=======



TensorLayerX has some prerequisites that need to be installed first, including TensorFlow ,

MindSpore, PaddlePaddle,numpy and matplotlib.For GPU support CUDA and cuDNN are required.



.. code:: bash



    # for last stable version

    pip install --upgrade tensorlayerX



    # for latest release candidate

    pip install --upgrade --pre tensorlayerX



    # if you want to install the additional dependencies, you can also run

    pip install --upgrade tensorlayerX[all]              # all additional dependencies

    pip install --upgrade tensorlayerX[extra]            # only the `extra` dependencies

    pip install --upgrade tensorlayerX[contrib_loggers]  # only the `contrib_loggers` dependencies



Alternatively, you can install the latest or development version by directly pulling from OpenI:



.. code:: bash



    pip3 install git+https://github.com/tensorlayer/TensorLayerX.git



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





Cite

====



If you find this project useful, we would be grateful if you cite the

TensorLayer papers.



::



    @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}

    }

    @inproceedings{tensorlayer2021,

        title={Tensorlayer 3.0: A Deep Learning Library Compatible With Multiple Backends},

        author={Lai, Cheng and Han, Jiarong and Dong, Hao},

        booktitle={2021 IEEE International Conference on Multimedia \& Expo Workshops (ICMEW)},

        pages={1--3},

        year={2021},

        organization={IEEE}

    }



License

=======



TensorLayerX is released under the Apache 2.0 license.



.. |TENSORLAYER-LOGO| image:: https://git.openi.org.cn/TensorLayer/tensorlayer3.0/src/branch/master/img/tl_transparent_logo.png

   :target: https://tensorlayerx.readthedocs.io/en/latest/

