Building a engine takes too long

AI & Data Science Deep Learning (Training & Inference) TensorRT
#1

Description

Hi! I am trying to build yolov7 by compiling it and saving the serialzed trt engine.
However, the process is too slow. Takes 1hour for 256*256 resolution.
Is there anyway to speed up?

Environment

TensorRT Version: 8.2.4.2
GPU Type: RTX3080 12GB
Nvidia Driver Version: 515.48
CUDA Version: 11.4
CUDNN Version: 8.2.4
Operating System + Version: Ubuntu 20.04
Python Version (if applicable): 3.8
TensorFlow Version (if applicable):
PyTorch Version (if applicable): 1.12.0
Baremetal or Container (if container which image + tag):

Relevant Files

here is my onnx file.

Steps To Reproduce

Please include:

  • Exact steps/commands to build your repro
  • Exact steps/commands to run your repro
  • Full traceback of errors encountered
#2

Hi,
Request you to share the ONNX model and the script if not shared already so that we can assist you better.
Alongside you can try few things:

  1. validating your model with the below snippet

check_model.py

import sys
import onnx
filename = yourONNXmodel
model = onnx.load(filename)
onnx.checker.check_model(model).
2) Try running your model with trtexec command.

In case you are still facing issue, request you to share the trtexec “”–verbose"" log for further debugging
Thanks!

#4

Hi,

We Could not observe similar behavior.

You can try increasing the GPU memory utilization using --workspace option and please refer Developer Guide :: NVIDIA Deep Learning TensorRT Documentation

Also, we recommend you to please try on the latest TensorRT version 8.4 GA Update 1 and if you still face this issue share with us verbose logs and command to try from our end for better debugging.
https://developer.nvidia.com/nvidia-tensorrt-8x-download

Thank you.