TensorRT 10.5 Flux Dit BF16 precision
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Description
Description
When I used TensorRT 10.5 to infer Flux Dit on A800 using BF16 dataType, I found that there was a significant decrease in accuracy, while there was no significant decrease in accuracy when I used Pytorch BF16 to infer
Environment
TensorRT Version:
NVIDIA GPU: A800
NVIDIA Driver Version: 535.54.03
CUDA Version:12.2
CUDNN Version:
Operating System:
Python Version (if applicable):
Tensorflow Version (if applicable):
PyTorch Version (if applicable):
Baremetal or Container (if so, version):
Relevant Files
Model link:
Steps To Reproduce
Commands or scripts:
Have you tried the latest release?:
Can this model run on other frameworks? For example run ONNX model with ONNXRuntime (polygraphy run <model.onnx> --onnxrt):
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by collecting the missing TensorRT version, model link, commands or scripts, and complete environment details. Reproduce Flux Dit BF16 inference on the A800 with TensorRT and PyTorch, then compare their accuracy; done requires a reproducible accuracy difference and enough information to investigate it.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- pytorch
- Domain
- machine-learning, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100