AtomQuant: Quantization For Human.
Project description
Atom Quant
Atom Quant AKA: aq
is a easy quantization lib supports most decent and fashion quantization method through torch.fx
. Unlike original pytorch fx quantization support, we add a fully deploy chain from PTQ and QAT quantization to exporting onnx and then shiping to target inference framework.
atomquant can be easily use to quant any model without a specific dataloader or evaluator, you can even evaluator quantization performance without any GT.
We also support different quantization from vendor package, such as onnxruntime
, pytorch_quantization
, make it more easy to use and with fully examples.
There are 3 main components in atomquant:
- onnx: directly quantize on onnx model (via onnxruntime);
- atom: Our built-in quantization method;
- tensorrt: Quantization specific for convert to TensorRT engine usage;
Install
atomquant can be installed via:
pip install atomquant
Model Zoo
Here, we provide some models quantized for coco, it devided into CPU use, or TensorRT use. Related training code also available:
Examples
-
Quant Classification
-
Quant GPT3
-
Quant VITS
-
Quant AlphaPose
-
Quant YOLOv7
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file atomquant-0.0.1.tar.gz
.
File metadata
- Download URL: atomquant-0.0.1.tar.gz
- Upload date:
- Size: 1.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.26.0 requests-toolbelt/0.9.1 urllib3/1.26.7 tqdm/4.62.3 importlib-metadata/4.10.1 keyring/23.5.0 rfc3986/1.5.0 colorama/0.4.4 CPython/3.9.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0a82ab4d973b50d54fb3664f045f705dd96c736c8e4edfcbe8d4d0f773212a1d |
|
MD5 | 7818565ab3ee00dbe9429e473989a3d3 |
|
BLAKE2b-256 | e7d9bda26c00612087767a3aaec57b50f87be27dd0de7117e180701fed7eea74 |