Comments (3)
Tracking ticket: [DLIS-6397]
from server.
Hi @gulldan, compose.py
doesn't currently support the TensorRT-LLM backend (DLIS-6397).
You should be able to achieve something similar by using build.py
with:
--backend tensorrtllm:r24.04
--backend python:r24.04
--backend onnxruntime:r24.04
Let us know if this helps for your use case.
from server.
thank you.
i tried
./build.py --backend tensorrtllm:r24.04 --backend python:r24.04 --backend onnxruntime:r24.04 --enable-gpu --build-type Release --target-platform linux --endpoint grpc --endpoint http
but its failed
build_log.txt
Host info
Linux 6.5.0-35-generic #35-Ubuntu SMP PREEMPT_DYNAMIC Fri Apr 26 11:23:57 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux
Docker version 26.1.2, build 211e74b
cmake version 3.28.4
python 3.11.6
GeForce RTX 4090
Driver Version: 550.54.15
from server.
Related Issues (20)
- ONNX backend with TensorRT optimizer sometimes fails to start HOT 1
- Any example of triton-vllm with c++ client?
- Tritonserver for FIL backend not starting HOT 1
- Why is my model in ensemble receiving out-of-order input HOT 3
- Add TT-Metalium as a backend HOT 1
- unexpected datatype TYPE_INT64 for inference input ,expecting TYPE_INT32 HOT 2
- triton malloc fail HOT 9
- Peaks in instantaneous traffic lead to high TP99 inference latency. HOT 2
- Low QPS with momentary traffic surges cause significant increases in inference TP99 latency. HOT 1
- Single docker layer is too large HOT 2
- Memory over 100% with decoupled dali video model HOT 1
- When the request is large, the Triton server has a very high TTFT. HOT 1
- Uneven QPS leads to low throughput and high latency as well as low GPU utilization HOT 8
- Triton Server 24.05 can't initialize CUDA drivers if host system has installed Nvidia driver 555.85 HOT 2
- Building and developing with libtritonserver.so HOT 1
- CUDA runtime API error raised when using only cpu on Mac M3 HOT 1
- Segmentation fault (core dumped) - Server version 2.46.0 HOT 4
- Segmentation fault when multi-requsts to triton-vllm HOT 8
- Does Triton Server support Dynamic Request Batching for models which has sparse tensors as inputs HOT 3
- Triton Tensorrt-LLM 24.04 and 24.05 are very large HOT 3
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from server.