Skip to main content
nncase

License compiler-build

nncase is a neural network compiler for AI accelerators.

nncase 是一个为 AI 加速器设计的神经网络编译器。

技术交流 QQ 群:790699378

Telegram: nncase community

Install from binaries

从二进制安装

Download prebuilt binaries from Release.

下载预编译的二进制文件 Release。

Build from source

从源码编译

Build from source

Supported operators

支持的算子

Usage

使用方法

Resources

资源


Architecture

架构

nncase arch

Features

  • Supports multiple inputs and outputs and multi-branch structure
  • Static memory allocation, no heap memory acquired
  • Operators fusion and optimizations
  • Support float and quantized uint8 inference
  • Support post quantization from float model with calibration dataset
  • Flat model with zero copy loading

功能

  • 支持多输入输出网络,支持多分支结构
  • 静态内存分配,不需要堆内存
  • 算子合并和优化
  • 支持 float 和量化 uint8 推理
  • 支持训练后量化,使用浮点模型和量化校准集
  • 平坦模型,支持零拷贝加载

Metadata

Release files for nncase 1.7.0.20220530

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

Built distributions (wheels)

Table of built distributions (wheels) for nncase 1.7.0.20220530
File
nncase-1.7.0.20220530-cp310-cp310-win_amd64.whl CPython 3.10 CPython 3.10 Windows x86-64 Details
nncase-1.7.0.20220530-cp310-cp310-manylinux_2_24_x86_64.whl CPython 3.10 CPython 3.10 Linux glibc 2.24+ x86-64 Details
nncase-1.7.0.20220530-cp310-cp310-macosx_10_15_x86_64.whl CPython 3.10 CPython 3.10 macOS 10.15+ x86-64 Details
nncase-1.7.0.20220530-cp39-cp39-win_amd64.whl CPython 3.9 CPython 3.9 Windows x86-64 Details
nncase-1.7.0.20220530-cp39-cp39-manylinux_2_24_x86_64.whl CPython 3.9 CPython 3.9 Linux glibc 2.24+ x86-64 Details
nncase-1.7.0.20220530-cp39-cp39-macosx_10_15_x86_64.whl CPython 3.9 CPython 3.9 macOS 10.15+ x86-64 Details
nncase-1.7.0.20220530-cp38-cp38-win_amd64.whl CPython 3.8 CPython 3.8 Windows x86-64 Details
nncase-1.7.0.20220530-cp38-cp38-manylinux_2_24_x86_64.whl CPython 3.8 CPython 3.8 Linux glibc 2.24+ x86-64 Details
nncase-1.7.0.20220530-cp38-cp38-macosx_10_15_x86_64.whl CPython 3.8 CPython 3.8 macOS 10.15+ x86-64 Details
nncase-1.7.0.20220530-cp37-cp37m-win_amd64.whl CPython 3.7 CPython 3.7 pymalloc Windows x86-64 Details
nncase-1.7.0.20220530-cp37-cp37m-manylinux_2_24_x86_64.whl CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.24+ x86-64 Details
nncase-1.7.0.20220530-cp37-cp37m-macosx_10_15_x86_64.whl CPython 3.7 CPython 3.7 pymalloc macOS 10.15+ x86-64 Details
nncase-1.7.0.20220530-cp36-cp36m-win_amd64.whl CPython 3.6 CPython 3.6 pymalloc Windows x86-64 Details
nncase-1.7.0.20220530-cp36-cp36m-manylinux_2_24_x86_64.whl CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.24+ x86-64 Details
nncase-1.7.0.20220530-cp36-cp36m-macosx_10_15_x86_64.whl CPython 3.6 CPython 3.6 pymalloc macOS 10.15+ x86-64 Details

Total release size: 124.3 MB

Release files / nncase-1.7.0.20220530-cp310-cp310-win_amd64.whl

Download URL nncase-1.7.0.20220530-cp310-cp310-win_amd64.whl
Size 5.5 MB
Tags CPython 3.10 Windows x86-64
SHA-256 checksum
How to use checksums
15decd50b8042ff69a1e2e4fa7d02517f5ce272630a90a1421d4e9014d273aa6
BLAKE2b-256 checksum
How to use checksums
3dddaffc6dcc7d5e9b0a99df19795c18a9ff8bc9bf1bb5b3c75fdfdc9a66c460
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / nncase-1.7.0.20220530-cp310-cp310-manylinux_2_24_x86_64.whl

Download URL nncase-1.7.0.20220530-cp310-cp310-manylinux_2_24_x86_64.whl
Size 10.7 MB
Tags CPython 3.10 Linux glibc 2.24+ x86-64
SHA-256 checksum
How to use checksums
c8d5b4be8f7e3649bccd3cc9a66a0e7698787046df8d0b56afe7208e9e0d504b
BLAKE2b-256 checksum
How to use checksums
0b426437ef0b31e06623e9224dc75383c1cd4408a4e32f391c90b5ef51715501
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / nncase-1.7.0.20220530-cp310-cp310-macosx_10_15_x86_64.whl

Download URL nncase-1.7.0.20220530-cp310-cp310-macosx_10_15_x86_64.whl
Size 8.7 MB
Tags CPython 3.10 macOS 10.15+ x86-64
SHA-256 checksum
How to use checksums
35fafa8c267f9a19d2731a597268fb2b2e144a16a75c22f8a44bb7fc09f8cfa7
BLAKE2b-256 checksum
How to use checksums
cf8b1d2afabff2c54925fc878c8fd90b34dbf988e7b640c33d7d432364d16780
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / nncase-1.7.0.20220530-cp39-cp39-win_amd64.whl

Download URL nncase-1.7.0.20220530-cp39-cp39-win_amd64.whl
Size 5.5 MB
Tags CPython 3.9 Windows x86-64
SHA-256 checksum
How to use checksums
b503a83c2e92d06f6fcd37e7cb1ee14c795e542f39099270a6437bcaacad0e70
BLAKE2b-256 checksum
How to use checksums
26a592efc34204fc645ca89dd121d96f6638d979c58bc554da63513ac55f99fb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / nncase-1.7.0.20220530-cp39-cp39-manylinux_2_24_x86_64.whl

Download URL nncase-1.7.0.20220530-cp39-cp39-manylinux_2_24_x86_64.whl
Size 10.7 MB
Tags CPython 3.9 Linux glibc 2.24+ x86-64
SHA-256 checksum
How to use checksums
4152fb88c8054d2c27259538cf089f42ec352a2fd4b646391031c596b21fcd2a
BLAKE2b-256 checksum
How to use checksums
4284306a384686a6ddeefde8560c2b3d032c0cdfb1e3d667e46d0a1dbc1a71db
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / nncase-1.7.0.20220530-cp39-cp39-macosx_10_15_x86_64.whl

Download URL nncase-1.7.0.20220530-cp39-cp39-macosx_10_15_x86_64.whl
Size 8.7 MB
Tags CPython 3.9 macOS 10.15+ x86-64
SHA-256 checksum
How to use checksums
ca3ce3964797638ebae8ca5b1faad17a749d50344a427cb2e1ea6ecb9616ce33
BLAKE2b-256 checksum
How to use checksums
a4de4448ad3d743a49425df4442f558beb268a22024a77d2f3ce7e0040c147bf
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / nncase-1.7.0.20220530-cp38-cp38-win_amd64.whl

Download URL nncase-1.7.0.20220530-cp38-cp38-win_amd64.whl
Size 5.5 MB
Tags CPython 3.8 Windows x86-64
SHA-256 checksum
How to use checksums
ef90f85f5e72331b5aa1662a288583e1925ebe4fd9c560d46d0c85c5bf2e899b
BLAKE2b-256 checksum
How to use checksums
3ac0a0667ff65d40c0c6b9900985422602d6c90f7a0ee9956445806de30e8ad1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / nncase-1.7.0.20220530-cp38-cp38-manylinux_2_24_x86_64.whl

Download URL nncase-1.7.0.20220530-cp38-cp38-manylinux_2_24_x86_64.whl
Size 10.7 MB
Tags CPython 3.8 Linux glibc 2.24+ x86-64
SHA-256 checksum
How to use checksums
dda390f167e1505aac3a474e05427092463186753add844a4bd6a57a38f88ea2
BLAKE2b-256 checksum
How to use checksums
4648cdaf24db9fd3883103355879dc351075d41ea36c6e1b647eb53008e46657
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / nncase-1.7.0.20220530-cp38-cp38-macosx_10_15_x86_64.whl

Download URL nncase-1.7.0.20220530-cp38-cp38-macosx_10_15_x86_64.whl
Size 8.7 MB
Tags CPython 3.8 macOS 10.15+ x86-64
SHA-256 checksum
How to use checksums
4aab828df30748486458417949a91fb62066dfd4a8667c355f486d4e01d598ab
BLAKE2b-256 checksum
How to use checksums
8f3450a3dce85a8098b50aa86c9fe46164cdfa0845ab5e75b9e46df4cf9cfba5
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / nncase-1.7.0.20220530-cp37-cp37m-win_amd64.whl

Download URL nncase-1.7.0.20220530-cp37-cp37m-win_amd64.whl
Size 5.5 MB
Tags CPython 3.7 CPython 3.7 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
e4eeca809be2ee4dbed888f301064cac9275561a1b76f037c4cb8e2d40340dc9
BLAKE2b-256 checksum
How to use checksums
790105f398faf7bc4f6bd09974e87e90791f8e5cd601f991e93390e8504e887a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / nncase-1.7.0.20220530-cp37-cp37m-manylinux_2_24_x86_64.whl

Download URL nncase-1.7.0.20220530-cp37-cp37m-manylinux_2_24_x86_64.whl
Size 10.7 MB
Tags CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.24+ x86-64
SHA-256 checksum
How to use checksums
e3d89250ca9f3d27bd74951db558911a323ef1e154487cb9fda47ddcc7beae95
BLAKE2b-256 checksum
How to use checksums
61e8b13c8b12f1f50c15e8721d2bb166e42d0ac173c297414dac9ab407b1a9d1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / nncase-1.7.0.20220530-cp37-cp37m-macosx_10_15_x86_64.whl

Download URL nncase-1.7.0.20220530-cp37-cp37m-macosx_10_15_x86_64.whl
Size 8.7 MB
Tags CPython 3.7 CPython 3.7 pymalloc macOS 10.15+ x86-64
SHA-256 checksum
How to use checksums
659c83e8823b089f6b14110604c695499390346437aae262aa9e75626777ee20
BLAKE2b-256 checksum
How to use checksums
f82e33a5f0320c4a5761768f874380dfb353f0c651b7232aa61b73ccd3ed2983
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / nncase-1.7.0.20220530-cp36-cp36m-win_amd64.whl

Download URL nncase-1.7.0.20220530-cp36-cp36m-win_amd64.whl
Size 5.5 MB
Tags CPython 3.6 CPython 3.6 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
0ee23b9253025ef72320463325b19d4a0d838d7e790a03cb3f303a85258782e9
BLAKE2b-256 checksum
How to use checksums
32d1432f6f070c0e7a930d95580147e578cfd518116cee2d1723ca529cfce6a9
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / nncase-1.7.0.20220530-cp36-cp36m-manylinux_2_24_x86_64.whl

Download URL nncase-1.7.0.20220530-cp36-cp36m-manylinux_2_24_x86_64.whl
Size 10.7 MB
Tags CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.24+ x86-64
SHA-256 checksum
How to use checksums
9e44bd84127ce065170dcff61a7fdfeda446210d6a91f138baf1f7e452f612e6
BLAKE2b-256 checksum
How to use checksums
441b389b24c0387d50a9bb49ffa30e39f893ad6f9d9b1fa6c76cd958c1def134
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Release files / nncase-1.7.0.20220530-cp36-cp36m-macosx_10_15_x86_64.whl

Download URL nncase-1.7.0.20220530-cp36-cp36m-macosx_10_15_x86_64.whl
Size 8.7 MB
Tags CPython 3.6 CPython 3.6 pymalloc macOS 10.15+ x86-64
SHA-256 checksum
How to use checksums
454ac2253f20098b6bcce58c8b641446d822be13e93f0664251c58645eaefbbb
BLAKE2b-256 checksum
How to use checksums
5c582f68716b41bde3047de5ed8081ee7bd1b90aae4218ba516d8766a6f2b47f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.12

Security for nncase 1.7.0.20220530

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page