rai-project/registry rai-project/registry

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  • Language
    Go
  • License
    University of Ill...
  • Created almost 8 years ago
  • Updated over 5 years ago
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rai-project

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Repository Details

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1

mlmodelscope

MLModelScope is an open source, extensible, and customizable platform to facilitate evaluation and measurement of ML models within AI pipelines.
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go-tensorrt

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tensorflow-go-examples

Examples of using TensorFlow Go API for different Deep Learning models
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go-pytorch

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go-fasttext

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7

go-mxnet

Go binding to MXNet C API to do inference with pre-trained model in Go
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8

go-cupti

Use NVIDIA CUPTI from within GO
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9

mxnet

MXNet agent for MLModelScope
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10

raid

The RAI sever evaluates build requests within a container environment. RAI is a scalable job submission system designed for diverse workloads. RAI’s design addresses challenges of scalability, configurability, security, and cost in delivering a flexible programming environments.
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11

pytorch

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12

nvidia-smi

NVIDIA-SMI abstractions. Used to detect the GPU hardware on the system
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13

tensorflow

TensorFlow agent for MLModelScope
Go
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14

go-caffe2

Caffe2 bindings for MLModelScope
C++
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15

cupti_samples

CUPTI samples from NVIDIA
Cuda
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16

dlframework

Common code for all deep learning predictors used by MLModelScope
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17

go-caffe

Go binding to Caffe C API to do inference with pre-trained model in Go
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18

store

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19

tensorrt

TensorRT agent for MLModelScope
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20

config

Configuration entry point for both RAI and CarML
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21

rai-srcmanager

rai-srcmanager is the utility for managing the rai repositories.
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22

evaluation

Evaluation tools for model performance / accuracy for MLModelScope
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23

plini

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24

caffe2

caffe2 agent used by CarML
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25

dockerfile-builder

The aim of D4P is to enrich the PowerPC container ecosystem by providing both a platform for developers to create docker containers, and for PowerPC community to find docker images. We have already built and published over 200 docker images using this platform, and they are available both in the D4P's image catalog or accessible through the C3SR center's Docker Hub link.
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26

dlplugin

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27

release-tools

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28

bumpversion

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29

profile

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30

vipertags

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31

model

Database models used by RAI and MLModelScope
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32

pipeline

Go
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33

cmd

Tools for the command line for both RAI and CarML
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34

ldcache

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35

tegra

Tools specific to the tegra systems (TX1 and TX2)
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36

web

A collection of web uilities
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1
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37

performance

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1
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38

cpu

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39

cgo

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40

acl

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41

parallel

Parallel tools used by RAI and CarML
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42

caffe

Caffe agent for MLModelScope
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43

inle

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44

tracer

Common tracer abstraction
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45

serializer

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46

cntk

CNTK agent for CarML
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47

dldataset

Builtin deep learning datasets used by MLModelScope
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48

context

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49

database

Database abstraction used by RAI and CarML
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50

scratch

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51

broker

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52

carml-models

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53

utils

Common utility functions
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54

coreml

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55

loadbalance

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56

linguist

Lasso
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57

archive

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58

sys

low-level system config (rlimits and stat)
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59

synthetic_load

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60

build_tools

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61

health

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62

Dockerfiles

Makefile
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63

downloadmanager

Utility functions for downloading data from the web
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64

uuid

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