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CUDA EP already supports [CUDA graph](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#cuda-graphs), also we observed some models can benefit from using CUDA graph with `trtexec`. Therefore, this PR enables the CUDA graph support for TRT EP. The implementation is based on https://github.com/microsoft/onnxruntime/pull/9978 with the same [constraints](https://github.com/microsoft/onnxruntime/pull/9978) as below: - Models with control-flow ops (i.e. If, Loop and Scan ops) are not supported. - Usage of CUDA Graphs is limited to models where-in all the model ops (graph nodes) can be partitioned to the TRT EP. - The input/output types of models need to be tensors. - Shapes of inputs/outputs cannot change across inference calls. - IObinding is required. |
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| common | ||
| eager | ||
| framework | ||
| graph | ||
| optimizer | ||
| platform | ||
| providers | ||
| session | ||