ciyongch opened a new pull request #14407: Update imagenet quantization script for MKL-DNN URL: https://github.com/apache/incubator-mxnet/pull/14407 ## Description ## This PR is to skip quantizing FullyConnected layers when its inputs are signed int8 and the subgraph backend is set to MKLDNN, due to the limitation in current version of MKL-DNN. This feature will be enabled when MKL-DNN is upgraded to 0.18 or higher. For not using MKLDNN subgraph backend (in general mode), users can still use both int8 and uint8 quantized FullyConnected for CPU platform (in this case, int8 will go to IGEMM path, but not providing requantize/dequantize fusion feature). ## Checklist ## ### Essentials ### Please feel free to remove inapplicable items for your PR. - [] The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to the relevant [JIRA issue](https://issues.apache.org/jira/projects/MXNET/issues) created (except PRs with tiny changes) - [ ] Changes are complete (i.e. I finished coding on this PR) - [ ] All changes have test coverage: - Unit tests are added for small changes to verify correctness (e.g. adding a new operator) - Nightly tests are added for complicated/long-running ones (e.g. changing distributed kvstore) - Build tests will be added for build configuration changes (e.g. adding a new build option with NCCL) - [ ] Code is well-documented: - For user-facing API changes, API doc string has been updated. - For new C++ functions in header files, their functionalities and arguments are documented. - For new examples, README.md is added to explain the what the example does, the source of the dataset, expected performance on test set and reference to the original paper if applicable - Check the API doc at http://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$PR_ID/$BUILD_ID/index.html - [ ] To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change ### Changes ### - [ ] Feature1, tests, (and when applicable, API doc) - [ ] Feature2, tests, (and when applicable, API doc) ## Comments ## - If this change is a backward incompatible change, why must this change be made. - Interesting edge cases to note here @pengzhao-intel @TaoLv
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