Triton Model Navigator v0.7.0
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new: Inplace Optimize feature - optimize models directly in the Python code
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new: Non-tensor inputs and outputs support
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new: Model warmup support in Triton model configuration
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new: nav.tensorrt.optimize api added for testing and measuring performance of TensorRT models
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new: Extended custom configs to pass arguments directly to export and conversion operations like
torch.onnx.export
orpolygraphy convert
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new: Collect GPU clock during model profiling
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new: Add option to configure minimal trials and stabilization windows for performance verification and profiling
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change: Navigator package version change to 0.2.3. Custom configurations now use trt_profiles list instead single value
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change: Store separate reproduction scripts for runners used during correctness and profiling
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Version of external components used during testing:
- PyTorch 2.1.0a0+b5021ba
- TensorFlow 2.12.0
- TensorRT 8.6.1
- ONNX Runtime 1.15.1
- Polygraphy: 0.47.1
- GraphSurgeon: 0.3.27
- tf2onnx v1.14.0
- Other component versions depend on the used framework containers versions.
See its support matrix
for a detailed summary.