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The output should be the same both when using an MXNet executor and when using a TensorRT executor. The performance speedup should be roughly 1.8x depending on the hardware and libraries used.
Roadmap
Finished Items
Initial integration has been completed and launched as of MXNet 1.3. We've tested this integration against a variety of models, including all the gluonCV models, Wavenet and some custom computer vision models. Performance is roughly in line with expectations, but we're seeing a few regressions over earlier measurements that require investigation.
Continuous Integration support is enabled and running continually for all active PRs opened with MXNet.
PIP packages and Docker images have been published along with the MXNet 1.3 release.
Future work
FP16 Integration
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