semvec/pypi-packages huggingface dataset:
torchgpipe 0.0.7
GPipe for PyTorch
License: BSD-3-Clause
Keywords: pytorch gpipe


torchgpipe
==========

A GPipe_ implementation in PyTorch_.

.. _GPipe: https://arxiv.org/abs/1811.06965
.. _PyTorch: https://pytorch.org/

.. sourcecode:: python

   from torchgpipe import GPipe

   model = nn.Sequential(a, b, c, d)
   model = GPipe(model, balance=[1, 1, 1, 1], chunks=8)

   for input in data_loader:
       output = model(input)

What is GPipe?
~~~~~~~~~~~~~~

GPipe is a scalable pipeline parallelism library published by Google Brain,
which allows efficient training of large, memory-consuming models. According to
the paper, GPipe can train a 25x larger model by using 8x devices (TPU), and
train a model 3.5x faster by using 4x devices.

`GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism
<https://arxiv.org/abs/1811.06965>`_

Google trained AmoebaNet-B with 557M parameters over GPipe. This model has
achieved 84.3% top-1 and 97.0% top-5 accuracy on ImageNet classification
benchmark (the state-of-the-art performance as of May 2019).

Links
~~~~~

- Source Code: https://github.com/kakaobrain/torchgpipe
- Documentation: https://torchgpipe.readthedocs.io/
- Original Paper: https://arxiv.org/abs/1811.06965