From d74fc68b8fdefeab8d770436c78a6ef641d46145 Mon Sep 17 00:00:00 2001 From: Wang Xinyu Date: Sat, 2 May 2020 20:31:26 +0800 Subject: [PATCH] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index b4e5586..fc77f49 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ So why don't we just skip all parsers? We just use TensorRT network definition A I wrote this project to get familiar with tensorrt API, and also to share and learn from the community. -TensorRTx has a brother project [Pytorchx](https://github.com/wang-xinyu/pytorchx). All the models are implemented in pytorch first, and export a weights file xxx.wts, and then use tensorrt to load weights, define network and do inference. +All the models are implemented in pytorch first, and export a weights file xxx.wts, and then use tensorrt to load weights, define network and do inference. Some pytorch implementations can be found in my repo [Pytorchx](https://github.com/wang-xinyu/pytorchx), the remaining are from polular open-source pytorch implementations. ## Getting Started @@ -18,7 +18,7 @@ There is a guide for quickly getting started, taking lenet5 as a demo. [Getting_ 2. GTX1080 / Ubuntu16.04 / cuda10.0 / cudnn7.6.5 / tensorrt7.0.0 / nvinfer7.0.0 / opencv3.3 -Currently, TX1 ans x86 GTX1080 were tested. trt4 api were using, some api are deprecated in trt7, but still can compile successfully. +Currently, TX1/TX2 and x86 GTX1080 were tested. trt4 api were using, some APIs are deprecated in trt7, but still can compile successfully. ## Models