I have a pytorch neural network which receives an image and produces a multi-dimensional output (e.g. size 30x15x15)
I managed to do the inference in TensorRT. I used the sampleOnnxMNIST sample on github.
What I can’t do is to extract the network outputs from the buffer:
float* output = static_cast<float*>(buffers.getHostBuffer(mParams.outputTensorNames));
output points to 30 values which I loop, but if I go outside the 30 bound, I get random numbers.
for (int i = 0; i < 30; i++)
std::cout << output[i] << "\n";
TensorRT Version: 22.214.171.124
GPU Type: Nvidia
Nvidia Driver Version:
CUDA Version: 11.5
Operating System + Version: Ubuntu 20.04
Python Version (if applicable): 3.7
TensorFlow Version (if applicable):
PyTorch Version (if applicable): 1.10.1
Baremetal or Container (if container which image + tag):
Can you try running your model with trtexec command, and share the “”–verbose"" log in case if the issue persist
You can refer below link for all the supported operators list, in case any operator is not supported you need to create a custom plugin to support that operation
Also, request you to share your model and script if not shared already so that we can help you better.
Meanwhile, for some common errors and queries please refer to below link: