This section addresses common questions about how to use MXNet. These include performance issues, e.g., how to train with multiple GPUs. They also include workflow questions, e.g., how to visualize a neural network computation graph. These answers are fairly focused. For more didactic, self-contained introductions to neural networks and full working examples, visit the tutorials section.
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How do I use gradient compression with distributed training?
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What are the best setup and data-handling tips and tricks for improving speed?
If you need help with using MXNet, have questions about applying it to a particular kind of problem, or have a discussion topic, please use our forum.
We track bugs and new feature requests in the MXNet Github repo in the issues folder: mxnet/issues.
MXNet is evolving fast. To see what's next and what we are working on internally, go to the MXNet Roadmap.