Description
Unable to convert an ONNX model to a trt engine using trtexec command or python package. Would love to give tensorrt a try but have been unable to use it for quite some time now. The model architecture is called “Segformer”, it’s a vision transformer for image segmentation.
Previously created another thread attempting to use trtexec to build the model on a cloud GPU as I thought I simply needed more memory but now that I know that was not the issue I am attempting to simply build directly on the Jetson device, especially since the developer guide explains that serialized engines are not transferable between GPUs. I understand that this problem may have been resolved in the latest version of TensorRT, is there any way that I can use these new features on my Jetson Xavier NX or am I stuck waiting for the next update to JetPack? If I am stuck waiting for the next update, is there a roadmap I can access somewhere? Is it a matter of weeks, months, or years until the new version of TensorRT can be used on my NVIDIA Jetson device? Thank you.
Environment
TensorRT Version: 8.4.3
GPU Type: Jetson Xavier NX
Nvidia Driver Version:
CUDA Version: 11.4
CUDNN Version:
Operating System + Version: NVIDIA Jetpack 5.0.2
Python Version (if applicable): 3.8.10
TensorFlow Version (if applicable): N/A
PyTorch Version (if applicable): 1.11.0
Baremetal or Container (if container which image + tag): N/A
Relevant Files
sidewalk3.onnx https://drive.google.com/file/d/1FDeorXZqMKHYNPaKeM16wF2fAcYw_HF9/view?usp=sharing
sidewalk4.onnx https://drive.google.com/file/d/17WZ-0BxfbOLTAGsoGlCBdfsm5zLx52jg/view?usp=sharing
Steps To Reproduce
(Based on this portion of the developer guide: Overview — NVIDIA TensorRT Documentation)
import tensorrt as trt
logger = trt.Logger(trt.Logger.WARNING)
builder = trt.Builder(logger)
network = builder.create_network(1 << int(trt.NetworkDefinitionCreationFlag.EXPLICIT_BATCH))
parser = trt.OnnxParser(network, logger)
success = parser.parse_from_file(model_path)
config = builder.create_builder_config()
serialized_engine = builder.build_serialized_network(network, config)