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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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2

rai

The RAI client allows one to interact with a cluster of machine to submit and evaluate code. 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.
Go
35
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3

go-tensorrt

Go binding to TensorRT C API to do inference with pre-trained model in Go
C++
27
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4

tensorflow-go-examples

Examples of using TensorFlow Go API for different Deep Learning models
Go
17
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5

go-pytorch

C++
15
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6

go-fasttext

HTML
14
star
7

go-mxnet

Go binding to MXNet C API to do inference with pre-trained model in Go
Go
10
star
8

go-cupti

Use NVIDIA CUPTI from within GO
Go
9
star
9

mxnet

MXNet agent for MLModelScope
Go
8
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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.
Go
7
star
11

pytorch

Go
6
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12

nvidia-smi

NVIDIA-SMI abstractions. Used to detect the GPU hardware on the system
Go
6
star
13

tensorflow

TensorFlow agent for MLModelScope
Go
6
star
14

go-caffe2

Caffe2 bindings for MLModelScope
C++
5
star
15

cupti_samples

CUPTI samples from NVIDIA
Cuda
5
star
16

dlframework

Common code for all deep learning predictors used by MLModelScope
Go
5
star
17

go-caffe

Go binding to Caffe C API to do inference with pre-trained model in Go
C++
5
star
18

store

Go
3
star
19

tensorrt

TensorRT agent for MLModelScope
Go
2
star
20

config

Configuration entry point for both RAI and CarML
Go
2
star
21

rai-srcmanager

rai-srcmanager is the utility for managing the rai repositories.
Go
2
star
22

evaluation

Evaluation tools for model performance / accuracy for MLModelScope
Mathematica
2
star
23

plini

Go
2
star
24

caffe2

caffe2 agent used by CarML
Go
2
star
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.
Go
2
star
26

dlplugin

1
star
27

release-tools

Go
1
star
28

bumpversion

Go
1
star
29

profile

Go
1
star
30

vipertags

Go
1
star
31

model

Database models used by RAI and MLModelScope
Go
1
star
32

pipeline

Go
1
star
33

cmd

Tools for the command line for both RAI and CarML
Go
1
star
34

ldcache

Go
1
star
35

tegra

Tools specific to the tegra systems (TX1 and TX2)
Shell
1
star
36

web

A collection of web uilities
Go
1
star
37

performance

Go
1
star
38

cpu

Go
1
star
39

cgo

Go
1
star
40

registry

Go
1
star
41

acl

Go
1
star
42

parallel

Parallel tools used by RAI and CarML
Go
1
star
43

caffe

Caffe agent for MLModelScope
Go
1
star
44

inle

Go
1
star
45

tracer

Common tracer abstraction
Go
1
star
46

serializer

Go
1
star
47

cntk

CNTK agent for CarML
Go
1
star
48

dldataset

Builtin deep learning datasets used by MLModelScope
Go
1
star
49

context

Go
1
star
50

database

Database abstraction used by RAI and CarML
Go
1
star
51

scratch

C
1
star
52

broker

Go
1
star
53

carml-models

1
star
54

utils

Common utility functions
Go
1
star
55

coreml

Go
1
star
56

loadbalance

Go
1
star
57

linguist

Lasso
1
star
58

archive

Go
1
star
59

sys

low-level system config (rlimits and stat)
Go
1
star
60

synthetic_load

Go
1
star
61

build_tools

Go
1
star
62

health

Go
1
star
63

downloadmanager

Utility functions for downloading data from the web
Go
1
star
64

uuid

Go
1
star