In this tutorial we are exploring NVIDIA's TensorRT, a deep learning inference optimizer.
We are walking step-by-step through a Jupyter notebook that boosts inference speeds for an object detection model using pyTorch.
This tutorial is intended to be beginner-friendly but requires prior knowledge in Python and familiarity with Neural Networks and Machine Learning.
Jupyter notebook:
github.com/CactusQ/tensor_rt_...
Further Reading:
developer.nvidia.com/tensorrt
/ understanding-nvidias-...
github.com/ultralytics/yolov5
cocodataset.org/
Edit:
In the video I said TensorScript but meant TorchScript.
At the very end I also mention "MAP" without explaining Mean Average precision:
kili-technology.com/data-labe...
Негізгі бет TensorRT for Beginners: A Tutorial on Deep Learning Inference Optimization
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