Caenorst opened a new pull request #15399: Add unit tests for TensorRT integration and fix some bugs URL: https://github.com/apache/incubator-mxnet/pull/15399 ## Description ## TensorRT integration lacked of unit tests, we instead relied on output comparison of a full network which is not very pertinent, difficult to find the tolerance and not very helpful if it fails. This PR have two purposes: 1) Add unit test for all operations: As we only partition subgraph of at least 2 Ops we always append an identity to each output. we then compare to MXNet, using both TRT FP32 and FP16 computation. 2) Fix a bunch of edge cases bugs that have been exposed by the unit tests: - NHWC is currently not compatible with TensorRT - Pooling is currently not compatible with count_include_pad and only compatible with pooling_convention Valid - FullyConnected without bias cannot be converted to MatMul (as there should be a transpose before) for the moment we decided to remove compatibility, it is quite rare to do FullyConnected without bias anyway - Concat is not compatible if the concatenation axis is the batch axis - The dropout have to be only enabled on training mode (act as identity) - BatchNorm with fix_gamma can have gamma != 1. so we force the value to be 1. when loading it. ## Checklist ## ### Essentials ### Please feel free to remove inapplicable items for your PR. - [X] Changes are complete (i.e. I finished coding on this PR) - [X] All changes have test coverage: - Unit tests are added for small changes to verify correctness (e.g. adding a new operator) - [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. - [X] To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change ## Comments ## - the test of output comparison in a full networks should probably be replaced by an accuracy comparison over a full dataset
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