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ceccocats / tkDNN

Deep neural network library and toolkit to do high performace inference on NVIDIA jetson platforms
GNU General Public License v2.0
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The current version has a huge performance gap compared with the previous version #226

Closed dongxuanlb closed 3 years ago

dongxuanlb commented 3 years ago

Xavier, yolov4, fp16 At version: adac8576b0faf515ad3f459b1f50fd16cef6d64d with 33fps At version: a638592fc74668471e87ac930b4695ce99dc7d43 with only 10fps

ceccocats commented 3 years ago

thank you, it was a compilation issue introduced by @perseusdg during the develop of #218 in this commit 56feb54377c0678e42077fabbf84ce2fc138f4c5

I tested on my PC and on Xavier and it look ok now; tell me if the issue persist

dongxuanlb commented 3 years ago

Hi, Im still got only 15fps.

dongxuan@xavier:~/workspace/tkDNN/build$ ./demo yolo4_fp16.rt ../demo/yolo_test.mp4 y detection yolo4_fp16.rt New NetworkRT (TensorRT v7.13) Float16 support: 1 Int8 support: 1 DLAs: 2 create execution context Input/outputs numbers: 4 input index = 0 -> output index = 3 Data dim: 1 3 416 416 1 Data dim: 1 255 13 13 1 RtBuffer 0 dim: Data dim: 1 3 416 416 1 RtBuffer 1 dim: Data dim: 1 255 52 52 1 RtBuffer 2 dim: Data dim: 1 255 26 26 1 RtBuffer 3 dim: Data dim: 1 255 13 13 1 camera started ^Crequest gateway stop detection end

Time stats: Min: 59.4205 ms Max: 216.611 ms Avg: 64.0227 ms 15.6195 FPS