ysh329

ysh329

Geek Repo

Company:freelancer

Location:Gensokyo

Home Page:http://yuenshome.space

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ysh329's repositories

deep-learning-model-convertor

The convertor/conversion of deep learning models for different deep learning frameworks/softwares.

embedded-ai.bi-weekly

WeChat: NeuralTalk,Weekly report and awesome list of embedded-ai.

OpenCL-101

Learn OpenCL step by step.

OpenMP-101

Learn OpenMP examples step by step

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sword-x-offer

66 classic and common interview problems from 《剑指offer》 with multiple-method-CPP solutions, and common data structure summary, etc

mace

MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.

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ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

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onnx

Open standard for machine learning interoperability

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tvm

End to end Tensor IR/DSL stack for deploying deep learning workloads to hardwares

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.tmux

🇫🇷 Oh my tmux! My self-contained, pretty & versatile tmux configuration made with ❤️

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bolt

Bolt is a deep learning library with high performance and heterogeneous flexibility.

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cmake_android_executable_template

This a template project for build executable for android (including normal mode and recovery mode)

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examples

A set of examples around MegEngine

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flaskDemo

使用 Python+Flask+MySQL+Redis 开发简单接口实例

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FluidDoc

Documentations for PaddlePaddle

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MegFlow

Efficient ML solutions for long-tailed demands.

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mindspore

MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.

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mmocr

OpenMMLab Text Detection, Recognition and Understanding Toolbox

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MNN

MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba

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Paddle-Lite-1

Multi-platform high performance deep learning inference engine (『飞桨』多平台高性能深度学习预测引擎)

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ppl.nn

A primitive library for neural network

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software-config

Configures including vim, Xshell and etc.

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taichi

Parallel programming for everyone.

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taichicon

TaichiCon: Taichi Conferences

YiYiYa

YiYiYa 一个os

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