Hi,
I followed to Blog: https://developer.nvidia.com/blog/speeding-up-deep-learning-inference-using-tensorrt/
But in step: Import the ONNX model into TensorRT, generate the engine, and perform inference, I got error:
[08/05/2021-10:43:41] [E] [TRT] 2: [ltWrapper.cpp::setupHeuristic::327] Error Code 2: Internal Error (Assertion cublasStatus == CUBLAS_STATUS_SUCCESS failed.)
[08/05/2021-10:43:41] [E] [TRT] 2: [builder.cpp::buildSerializedNetwork::417] Error Code 2: Internal Error (Assertion enginePtr != nullptr failed.)
I have checked TensorRT installationed and it fine.
Environment
TensorRT Version: 8.0.1 GPU Type: V100 Nvidia Driver Version: CUDA Version: 10.2 CUDNN Version: 7 Operating System + Version: 18.04 Python Version (if applicable): 3.6.9 PyTorch Version (if applicable):1.9.0+cu102
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:
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. https://github.com/NVIDIA/TensorRT/tree/master/samples/opensource/trtexec
In case you are still facing issue, request you to share the trtexec “”–verbose"" log for further debugging
Thanks!
We are unable to reproduce this issue on v100 gpu. We could successfully build tensorrt engine. We recommend you to please make sure you’ve installed dependencies and TensorRT correctly. If you still face this issue, please provide us trtexec command and complete verbose logs.