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2) Add its inputs / outputs to the queue (for future visit)
Future Work
FP16 Integration
The current integration of TensorRT into MXNet supports only FP32 float values for tensors. Allowing FP16 values would enable many further optimizations on Jetson and Volta devices.
https://jira.apache.org/jira/browse/MXNET-1084
Subgraph Integration
The new subgraph API is a natural fit for TensorRT. To help make the codebase consistent we'd like to port the current TensorRT integration to use the new API. The experimental integration into MXNet requires us to use contrib API calls. Once integration has moved to use the subgraph API users will be able to use TensorRT with a consistent API. Porting should also enable acceleration of gluon and module base models.
https://jira.apache.org/jira/browse/MXNET-1085
Increased Operator Coverage
The current operator cover is fairly limited. We'd like to enable all models that TensorRT is able to work with.
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Currently supported operators:
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elemwise_add
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Operators to be added:
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