NVIDIA Jetson Nano學習筆記(十一):如何運行PyTorch模型?

今天在電子報上看到PyTorch官方寫的一篇文章,Running PyTorch Models on Jetson Nano。內容寫得還不錯,蠻詳細的。

範例程式使用ResNet 50的PyTorch Pre-trained model轉成OONX格式後,搭配TensorRT進行推論。Inference time從31.5ms/19.4ms (FP32/FP16 precision)下降到僅需6.28ms (TensorRT)。

除此之外,該文章也介紹了如何針對YOLOv5進行TensorRT的優化推論。

詳細內容可參考下方連結:

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Machine Learning | Deep Learning | https://linktr.ee/yanwei

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