Tensorpack Documentation


Tensorpack is a training interface based on TensorFlow.

It’s Yet Another TF wrapper, but different in:

  • Focus on training speed.

    • Speed comes for free with tensorpack – it uses TensorFlow in the efficient way with no extra overhead. On various CNNs, it runs 1.5~1.7x 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. You cannot beat its speed unless you’re a TensorFlow expert.

    • See tensorpack/benchmarks for some benchmark scripts.

  • Focus on large datasets.

    • It’s painful to read/preprocess data through TF. Tensorpack helps you load large datasets (e.g. ImageNet) in pure Python with autoparallelization.

  • It’s not a model wrapper.

    • There are already too many symbolic function wrappers. Tensorpack includes only a few common models, but you can use any other wrappers within tensorpack, including sonnet/Keras/slim/tflearn/tensorlayer/….

See Tutorials to know more about these features: