-
### System Info
4*A800 80G
### Who can help?
@Tracin
### Information
- [X] The official example scripts
- [ ] My own modified scripts
### Tasks
- [X] An officially supported tas…
-
## Description
I'm using pytorch quantization toolkit to quantize my model, which has some conv3d module. The QAT procedure is OK. But when i use trtexec to convert the onnx with Q/DQ pairs to en…
-
## Description
When I use TensorRT for int8 quantization, I always encounter the accuracy fallback to fp32. The trt.BuilderFlag.OBEY_PRECISION_CONSTRAINTS parameter does not solve the issue. W…
-
By using [pytorch-quantization](https://docs.nvidia.com/deeplearning/tensorrt/pytorch-quantization-toolkit/docs/index.html) i was able to create TensorRT engine models that are (almost) fully int8 and…
-
## Description
almost same params
Even use int8 , it can't save more memory and slower than use deepcache. Is this supposed to be ? How to save more memory?
TensorRT supports dynami…
-
### Describe the issue
2022-10-20 09:21:09.531367276 [E:onnxruntime:Default, tensorrt_execution_provider.h:58 log] [2022-10-20 09:21:09 ERROR] 4: [network.cpp::validate::2891] Error Code 4: Interna…
-
## Description
Fresh install of `pip install tensorrt==10.2.0`
Following engine build crashes on Ubuntu 22.04.4 LTS:
```
from polygraphy.backend.trt import EngineFromNetwork
EngineFromNet…
-
### Describe the issue
I followed the tutorial on: https://github.com/microsoft/onnxruntime-inference-examples/tree/main/quantization/nlp/bert/trt to generate an int8 model.
However, whenever I run…
-
I tried to convert RT-DETR-R18 from onnx to tensorrt, and I succeeded in int8, failed in fp16.
torch2onnx in STATIC: python tools/export_onnx.py
onnx2trt: ./trtexec --onnx=rtdetr.onnx --saveEngin…
-
when I try to use torch2trt in yolactedge evaluation:
```
python eval.py --trained_model=../Downloads/yolact_edge_54_800000.pth --score_threshold=0.8 --top_k=100 --image=test_Color.jpg --use_tensorr…