Fix TensorRT build version check for 11#29779
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If onnxruntime is using TensorRT 10, the wrong version check ends up using TensorRT 11 code. This means strongly typed networks are converted to weak networks. This is a major performance penalty when using fp16 networks like Leela Chess Zero. Using `_MAJOR` version macro corrects the version check logic and fixes a major performance regression.
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Pull request overview
This PR fixes a TensorRT version-gating bug in the TensorRT Execution Provider where a preprocessor check used NV_TENSORRT_VERSION >= 11 (which is not comparable to a plain major version), causing TensorRT 10 builds to incorrectly take the TensorRT 11 code path and disable strongly-typed network creation—leading to significant performance regressions for fp16 strongly-typed networks.
Changes:
- Replace
#if NV_TENSORRT_VERSION >= 11with#if NV_TENSORRT_MAJOR >= 11when selectingcreateNetworkV2flags. - Apply the same fix in both the supported-subgraph parsing path and the fused-node build path to keep behavior consistent.
xadupre
approved these changes
Jul 20, 2026
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Description
If onnxruntime is using TensorRT 10, the wrong version check ends up using TensorRT 11 code. This means strongly typed networks are converted to weak networks. This is a major performance penalty when using fp16 networks like Leela Chess Zero. Using
_MAJORversion macro corrects the version check logic and fixes a major performance regression.Motivation and Context
This fixes a major performance regression in onnxruntime 1.27 when using strongly typed fp16 network. The performance drops to about 31% when using fp32 evaluation. The root cause for the performance drop was TensorRT seeing it as a weakly typed network and inserted type cast everywhere.
I bisected the problem to 53fcead . After careful review I noticed the accidental use of wrong version macros in a code path which set strongly typed flag. Fixing the check fixed the performance problem in my local test.