Skip to main content

High Level Tensorflow Deep Learning Library for Researcher and Engineer.

Project description

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.

# 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:

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

Containers with CPU support

# 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

# 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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tensorlayerx-0.5.7.tar.gz (358.5 kB view details)

Uploaded Source

Built Distribution

tensorlayerx-0.5.7-py3-none-any.whl (475.3 kB view details)

Uploaded Python 3

File details

Details for the file tensorlayerx-0.5.7.tar.gz.

File metadata

  • Download URL: tensorlayerx-0.5.7.tar.gz
  • Upload date:
  • Size: 358.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: Python-urllib/3.6

File hashes

Hashes for tensorlayerx-0.5.7.tar.gz
Algorithm Hash digest
SHA256 018576c1216669688e2a75b354ffdc37978a24658a01d7b1206df385f5e15050
MD5 59a9c397d93ab8f65cab0b89f152e9eb
BLAKE2b-256 f7b386b9af64c6c845d5d2ed71b0dbf8c2854d218e9ed93c270b179391fe19e3

See more details on using hashes here.

File details

Details for the file tensorlayerx-0.5.7-py3-none-any.whl.

File metadata

File hashes

Hashes for tensorlayerx-0.5.7-py3-none-any.whl
Algorithm Hash digest
SHA256 f58839a2f606fc79060ccbc1f8e7305b7e4dddee7e71d5855b09f5dc2f0c4a52
MD5 93103e72617c243988a07a1e288751f9
BLAKE2b-256 388bd1159ee998e94284bf9f5740ea2dc3b932e31b2917b827b1a0b8186f87eb

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page