Comments (4)
@enfipy Thanks! It is ready for simple Als as long as they don't require custom plugins to run in TRT. Work for adding plugin support is on going but might take a little bit since managing the C++ -> Rust -> C++ relationship is kind of tricky.
There are some pretty big QoL changes in the upcoming 0.4 release that I'm still putting the finishing touches on. If you're comfortable with it I would recommend use the crate directly from the develop
branch instead of the current published version on crates.io.
Let me know if you run into any issues or sharp edges while using the library!
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Brilliant! Thanks a lot for your hard work, I will definitely try this out!
from tensorrt-rs.
Picking up work on this.
from tensorrt-rs.
The overall project is looking awesome! What is the state of this and is it ready for simple AIs?
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Related Issues (20)
- Sample TensorFlow model for testing and examples HOT 2
- Write example application for using tensorrt-rs
- Support for basic plugin loading
- Implement bindings to TensorRT dims types
- Write Library Documentation
- Support for ndarray types as I/O for TensorRT models
- Static Linking of TensorRT libraries HOT 2
- CI Support on PR's HOT 1
- Implement onnx parser
- Complete bindings for nvinfer1::IBuilder HOT 1
- Complete bindings for nvinfer1::IExecutionContext HOT 1
- Complete bindings to nvinfer1::IRuntime HOT 1
- Complete bindings to nvinfer1::ICudaEngine HOT 1
- Complete bindings to nvinfer1::INetworkDefinition HOT 2
- Complete bindings to nvinfer1::IHostMemory
- Complete bindings to nvinfer1::IUffParser
- Fix tensorrt-rs tests on CI HOT 1
- Implement Error as enum
- Not able to build HOT 2
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