tree: d844e7a37b83bcdd003d203f73f995810812063d [path history] [tgz]
  1. get_data.py
  2. linear_classification.py
  3. linear_model.py
  4. readme.md
  5. weighted_softmax_ce.py
example/sparse/readme.md

Example

This folder contains examples using the sparse feature in MXNet.

Linear Classification

The example demonstrates the basic usage of the sparse feature in MXNet to speedup computation. It utilizes the sparse data loader, sparse operators and a sparse gradient updater to train a linear model on the Avazu click-through-prediction dataset.

  • python linear_classification.py

Notes on Distributed Training:

  • For distributed training, please use the ../../tools/launch.py script to launch a cluster.
  • For example, to run two workers and two servers with one machine, run ../../tools/launch.py -n 2 --launcher=local python linear_classification.py --kvstore=dist_async