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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2019/07/18 18:22:46 UTC
[GitHub] [incubator-mxnet] anirudhacharya edited a comment on issue #15589:
[Discussion] 1.6.0 Roadmap
anirudhacharya edited a comment on issue #15589: [Discussion] 1.6.0 Roadmap
URL: https://github.com/apache/incubator-mxnet/issues/15589#issuecomment-512930875
> 1. Can we work towards INT-64 support (Large Tensor) as DEFAULT. This would make it easy for Large Tensor use cases such as DGL, recommendation system models to use MXNet easily. Today, they need to compile from source. (CC @apeforest @access2rohit)
There are a few regressions that have been introduced since the large tensor support was added. For example, there are a few hierarchical attention networks which were training fine until 1.3.1 but since the addition of large tensor support, results in NaNs in weight vectors and gradient calculations. We probably should ensure all regressions are fixed with regard to this PR.
Related issues and PRs that might be relevant( the above issue is in addition to what is discussed in the below links) -
- https://github.com/apache/incubator-mxnet/pull/11742#issuecomment-449181485
- https://github.com/apache/incubator-mxnet/issues/14496
- https://github.com/apache/incubator-mxnet/pull/14570
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