torch2trt
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torch2trt | ort | |
---|---|---|
5 | 1 | |
4,395 | 345 | |
1.0% | 0.9% | |
3.1 | 6.3 | |
5 days ago | 3 months ago | |
Python | Python | |
MIT License | MIT License |
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torch2trt
- [D] How you deploy your ML model?
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PyTorch 1.10
Main thing you want for server inference is auto batching. It's a feature that's included in onnxruntime, torchserve, nvidia triton inference server and ray serve.
If you have a lot of preprocessing and post logic in your model it can be hard to export it for onnxruntime or triton so I usually recommend starting with Ray Serve (https://docs.ray.io/en/latest/serve/index.html) and using an actor that runs inference with a quantized model or optimized with tensorrt (https://github.com/NVIDIA-AI-IOT/torch2trt)
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Jetson Nano: TensorFlow model. Possibly I should use PyTorch instead?
https://github.com/NVIDIA-AI-IOT/torch2trt <- pretty straightforward https://github.com/jkjung-avt/tensorrt_demos <- this helped me a lot
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How to get TensorFlow model to run on Jetson Nano?
I find Pytorch easier to work with generally. Nvidia has a Pytorch --> TensorRT converter which yields some significant speedups and has a simple Python API. Convert the Pytorch model on the Nano.
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What are some alternatives?
TensorRT - PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
onnx-simplifier - Simplify your onnx model
transformer-deploy - Efficient, scalable and enterprise-grade CPU/GPU inference server for 🤗 Hugging Face transformer models 🚀
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
tensorrt_demos - TensorRT MODNet, YOLOv4, YOLOv3, SSD, MTCNN, and GoogLeNet
trt_pose - Real-time pose estimation accelerated with NVIDIA TensorRT
vision - Datasets, Transforms and Models specific to Computer Vision
functorch - functorch is JAX-like composable function transforms for PyTorch.
nn - 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
sparktorch - Train and run Pytorch models on Apache Spark.