Error Code 7: Internal Error (Add_430: dimensions not compatible for elementwise. Condition '==' violated: 5376 != 4725

[Egorundel]

Description

Hello, I made an ONNX model with dynamic dimensions of input [batch,3,height,width] by repository:
https://github.com/triple-Mu/YOLOv8-TensorRT/tree/triplemu/dynamic

After that I started trtexec with the following parameters:
trtexec --onnx=YOLOv8-dbs-dbd.onnx --saveEngine=YOLOv8-dbs-dbd.trt --explicitBatch=12 --minShapes=images:1x3x480x480 --optShapes=images:6x3x512x512 --maxShapes=images:12x3x640x640 --memPoolSize=workspace:3000

After that, I got a TensorRT engine from my model with dynamic dimensions and the batch size, then I start allocating CUDA memory, for example, for the size of 480 pixels. And I get an error
7: [shapeMachine.cpp::executeContinuation::887] Error Code 7: Internal Error (Add_430: dimensions not compatible for elementwise. Condition '==' violated: 5376 != 4725. Instruction: CHECK_EQUAL 5376 4725.)

The code swears at 430 Add node. It looks like this:

Why does it not work for me with dimension 480, if the model has dynamic dimensions at the input? And how to work properly with CUDA memory in general, if the model is with dynamic shapes?

Environment

TensorRT Version: 9.0.1

NVIDIA GPU: RTX3060

NVIDIA Driver Version: 535

CUDA Version: 11.1

CUDNN Version: 8.0.4

Operating System:

Python Version (if applicable): 3.8

Relevant Files

link to ONNX model: YOLOv8-dbs-dbd.onnx
link to TensorRT model: YOLOv8-dbs-dbd.trt

[Egorundel]

Model is correct. I checked by check_model.py

Text output from the terminal after using the trtexec I added to my GoogleDrive:
https://drive.google.com/drive/folders/1D19xWLW5mtTB6IRbmu8g87Y0vFQPZ3C6

[AakankshaS]

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:

Quick Start Guide :: NVIDIA Deep Learning TensorRT Documentation

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!

[Egorundel]

@AakankshaS I’ve already checked it. I wrote about it above :)

[spolisetty]

Hi,

We are unable to reproduce this issue on the latest TensorRT versions 8.61 and 9.0.1.
Please make sure you installed correct version of the TensorRT.

[09/21/2023-06:54:08] [I]
&&&& PASSED TensorRT.trtexec [TensorRT v8601] # trtexec --onnx=YOLOv8-dbs-dbd.onnx --saveEngine=YOLOv8-dbs-dbd.trt --explicitBatch=12 --minShapes=images:1x3x480x480 --optShapes=images:6x3x512x512 --maxShapes=images:12x3x640x640 --verbose

Thank you.