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Neural Network Toolbox on TensorFlow

Project Description

Neural Network Toolbox on TensorFlow.

See some examples to learn about the framework:

Speech / NLP:

The examples are not only for demonstration of the framework – you can train them and reproduce the results in papers.


It’s Yet Another TF wrapper, but different in: 1. Not focus on models. + There are already too many symbolic function wrappers. Tensorpack includes only a few common models, and helpful tools such as LinearWrap to simplify large models. But you can use any other wrappers within tensorpack, such as sonnet/Keras/slim/tflearn/tensorlayer/….

  1. Focus on training speed.
    • Speed comes for free with tensorpack. Even on a tiny CNN example, the training runs 1.6x faster than the equivalent Keras code.
    • Data-parallel multi-GPU training is off-the-shelf to use. It is as fast as Google’s official benchmark.
    • Data-parallel distributed training is off-the-shelf to use. It is as slow as Google’s official benchmark.
  2. Focus on large datasets.
    • It’s painful to read/preprocess data through TF. Use DataFlow to load large datasets (e.g. ImageNet) in pure Python with autoparallelization.
    • DataFlow has a unified interface, so you can compose and reuse them to perform complex preprocessing.
  3. Interface of extensible Callbacks. Write a callback to implement everything you want to do apart from the training iterations, and enable it with one line of code. Common examples include:
    • Change hyperparameters during training
    • Print some tensors of interest
    • Run inference on a test dataset
    • Run some operations once a while
    • Send loss to your phone

See tutorials to know more about these features.



  • Python 2 or 3

  • TensorFlow >= 1.0.0 (>=1.1.0 for Multi-GPU)

  • Python bindings for OpenCV (Optional, but required by a lot of features)

    pip install -U git+
    # or add `--user` to avoid system-wide installation.
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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
tensorpack-0.4.0-py2.py3-none-any.whl (215.3 kB) Copy SHA256 Checksum SHA256 3.6 Wheel Aug 10, 2017
tensorpack-0.4.0.tar.gz (152.6 kB) Copy SHA256 Checksum SHA256 Source Aug 10, 2017

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