We are trying to benchmark the Tensor rt optimization on Segmentation Models(In Tensorflow framework) Namely, Hardnet and Deeplab using trtexec .after some tryouts we were able to get optimized engines for Hardnet Models with better performance,but in case of Deeplab models their is an increase in latency(from 300.3921 ms to 5400 ms) after optimization.
While building the engine for the deeplab model we got a warning " TensorRT currently ignores the "seed"field in RandomUniform op. Random seeds will be used ",
we have got couple of questions
Is this warning and subsequent actions taken by tensor rt is inducing the increase in latency?
If it is, will removing this operation( RandomUniform ) would be a right approach?
If this warning is not related to hike in latency, what should be our approach to debug this issue.
TensorRT Version 220.127.116.11:
GPU Type Tesla T4:
Nvidia Driver Version 460.32.03:
CUDA Version 10.2:
CUDNN Version 18.104.22.168:
Operating System + Version= Ubuntu 18.04:
Python Version (if applicable) 3.7:
TensorFlow Version 2.5.0: