## Description ## Expand the scala imclassification example to be more general to different datasets and models. It now includes resnet as another model and the ability to use synthetic datasets that match the size of real datasets for benchmarking. Lastly, performance (cpu and memory) monitoring and logging was added.
## Checklist ## ### Essentials ### Please feel free to remove inapplicable items for your PR. - [x] The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to the relevant [JIRA issue](https://issues.apache.org/jira/projects/MXNET/issues) created (except PRs with tiny changes) - [x] Changes are complete (i.e. I finished coding on this PR) - [ ] All changes have test coverage: - Unit tests are added for small changes to verify correctness (e.g. adding a new operator) - Nightly tests are added for complicated/long-running ones (e.g. changing distributed kvstore) - Build tests will be added for build configuration changes (e.g. adding a new build option with NCCL) - [x] Code is well-documented: - For user-facing API changes, API doc string has been updated. - For new C++ functions in header files, their functionalities and arguments are documented. - For new examples, README.md is added to explain the what the example does, the source of the dataset, expected performance on test set and reference to the original paper if applicable - Check the API doc at http://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$PR_ID/$BUILD_ID/index.html - [x] To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change ### Changes ### - [x] Reorganize train model to better handle many models and datasets - [x] Add resnet model - [x] Add synthetic iterator for benchmarking - [x] Performance monitoring [ Full content available at: https://github.com/apache/incubator-mxnet/pull/12639 ] This message was relayed via gitbox.apache.org for [email protected]
