ONNX parse problem with TopK

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

Description

Hi,
I’m trying to convert a ssd onnx model to trt with onnx2trt exection file.
Because it has NonMaxSuppresion in the model, I made a plugin which inheritances IPluginV2DynamicExt to support dynamic shape.
After NonMaxSuppression it was abort at TopK layer and gives the message as below:

While parsing node number 498 [TopK -> “TopK_717”]:
ERROR: /home/u5393118/TensorRT/parsers/onnx/builtin_op_importers.cpp:3283 In function importTopK:
[8] Assertion failed: inputs.at(1).is_weights()

I’m not sure if modify TopK op will solve this issue or I shouldn’t modify it since it was built in op.
Or other solution is recommended?

Thank you.

Environment

TensorRT Version : 7.0.0-1
GPU Type : Tesla V100
Nvidia Driver Version : 450.51.05
CUDA Version : 11.0
CUDNN Version :
Operating System + Version : ubuntu 18.04
Python Version (if applicable) : 3.6.9
TensorFlow Version (if applicable) :
PyTorch Version (if applicable) :
Baremetal or Container (if container which image + tag) :

Relevant Files

ONNX model is downloaded from https://github.com/onnx/models/tree/master/vision/object_detection_segmentation/ssd

NonMaxSuppressionPlugin.cpp (7.4 KB) CMakeLists.txt (732 Bytes) NonMaxSuppressionPlugin.h (3.7 KB) builtin_op_importers.cpp (165.4 KB)

Steps To Reproduce

  1. In plugin folder mkdir NonMaxSuppressionPlugin
  2. Add file CMakeList.txt and NonMaxSuppressionPlugin.cpp and NonMaxSuppressionPlugin.h
  3. Modify parsers/onnx/builtin_op_importers.cpp
  4. Add initializePlugin< nvinfer1::plugin::NonMaxSuppressionPluginCreator >(logger, libNamespace) in InferPlugin.cpp
  5. Add NonMaxSuppression in CMakeList.txt in TensorRT/Plugin
  6. Run make and make install in TensorRT/build/
  7. Rebuild libnvinfer.so and libnvonnxparser.so
  8. Copy .so file in 7 to /usr/lib/x86_64-linux-gnu
  9. Change to bin/ run onnx2trt ssd-10.onnx -o ssd.trt
#2

Hi, Request you to share the ONNX model and the script so that we can assist you better.

Alongside you can try 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).

Alternatively, you can try running your model with trtexec command.

Thanks!

#3

Thanks for reply,
I have tried the onnx checker and no error was reported.

The model file has error when I upload the file from my PC.
Here’s the download link:

Thank you,
Kevin.

#4

Hi @disculus2012,

Please share Verbose log to debug.

Thank you.