pytorch_quant_tool

An experimental neural network quantization environment in Pytorch.

Post Training Quantization

NOTE: Fuse the well-trained model before operating Post Training Quantization.

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution for pytorch-quant-tool 1.3.1
File	Size	Uploaded
pytorch_quant_tool-1.3.1.tar.gz	2.8 kB	Nov 13, 2019	Details

Table of built distributions (wheels) for pytorch-quant-tool 1.3.1
File	Interpreter	ABI	Platform	Reset
pytorch_quant_tool-1.3.1-py3-none-any.whl 5.4 kB Nov 13, 2019	Python 3	none	any	Details

Total release size: 8.2 kB

Download URL	pytorch_quant_tool-1.3.1.tar.gz
Size	2.8 kB
Tags	Source
SHA-256 checksum How to use checksums	`8747f6b44bab47185e88fa54fb76884f4fd5258ca133e94c7190e1b33e8b4904`
BLAKE2b-256 checksum How to use checksums	`f42c952ded833c109727440b614b3494a0dc50c973afbf567e537fced9b6b1b2`
Upload date	Nov 13, 2019
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0.post20191030 requests-toolbelt/0.9.1 tqdm/4.38.0 CPython/3.6.9`

Download URL	pytorch_quant_tool-1.3.1-py3-none-any.whl
Size	5.4 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`6d6298db9ce659cffdedd02c1b3fcd2103e6dc22b8c3ffa19343634111af1041`
BLAKE2b-256 checksum How to use checksums	`f77b75c0caa84c28586231339b2cf634f617612b1498e32df3f36ba729cff08f`
Upload date	Nov 13, 2019
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0.post20191030 requests-toolbelt/0.9.1 tqdm/4.38.0 CPython/3.6.9`

This release

1.3.1 This release