Wandb-predictions - WANDB Predictions With Python

Overview

WANDB API

CI/CD

Below we capture the CI/CD scenarios that we would expect with our model endpoints.

  • In the automated build scenario, we capture any changes in the source code for the model server, build the new resultant docker image, push the image to the container registry, and then deploy via cloud run. This captures the CI component.

alt text

Automated builds based on changes in the master branch

  • In the scheduled build scenario, to ensure that we pull the latest model from wandb we force the fastapi application to rebuild, which in turn queries the service for the latest recorded model. This ensures we are always serving the most up-to-date model at the endpoint.

alt text

Scheduled builds on master to update the endpoint with the latest model

These scenarios together complete the CI/CD flow by allowing us to define a very easy to reproduce structure for defining build triggers based on different branches.

For brevity's sake I did not include the abstraction in this cloudbuild.yaml however you would simply pass in a substitution variable for the $MODEL_VERSION and pass that into the cloud console for that build for that branch. You could also abstract it by the name of the branch.

Screenshots

Cloud Build

alt text alt text alt text

This relies on Cloud Scheduler to schedule the manual trigger run

Cloud Run

alt text alt text alt text

Cloud Scheduler

alt text

Public API Result

alt text

Installation

python -m venv venv
source venv/bin/activate
make install

Runnning Localhost

make run

Deploy app

make deploy

Running Tests

make test

Running Easter Egg

make easter

Access Swagger Documentation

http://0.0.0.0:8080/docs

Access Redocs Documentation

http://0.0.0.0:8080/redoc

Project structure

Files related to application are in the app or tests directories. Application parts are:

app
├── api              - web related stuff.
│   └── routes       - web routes.
├── core             - application configuration, startup events, logging.
├── models           - pydantic models for this application.
├── services         - logic that is not just crud related.
└── main.py          - FastAPI application creation and configuration.
│
tests                  - pytest
Owner
Anish Shah
Tier 2 Support @ WANDB
Anish Shah
Python scripts for performing stereo depth estimation using the MobileStereoNet model in Tensorflow Lite.

TFLite-MobileStereoNet Python scripts for performing stereo depth estimation using the MobileStereoNet model in Tensorflow Lite. Stereo depth estimati

Ibai Gorordo 4 Feb 14, 2022
A simple API wrapper for Discord interactions.

Your ultimate Discord interactions library for discord.py. About | Installation | Examples | Discord | PyPI About What is discord-py-interactions? dis

james 641 Jan 03, 2023
Investigating Attention Mechanism in 3D Point Cloud Object Detection (arXiv 2021)

Investigating Attention Mechanism in 3D Point Cloud Object Detection (arXiv 2021) This repository is for the following paper: "Investigating Attention

52 Nov 19, 2022
ppo_pytorch_cpp - an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch

PPO Pytorch C++ This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment t

Martin Huber 59 Dec 09, 2022
Torchserve server using a YoloV5 model running on docker with GPU and static batch inference to perform production ready inference.

Yolov5 running on TorchServe (GPU compatible) ! This is a dockerfile to run TorchServe for Yolo v5 object detection model. (TorchServe (PyTorch librar

82 Nov 29, 2022
Open-CyKG: An Open Cyber Threat Intelligence Knowledge Graph

Open-CyKG: An Open Cyber Threat Intelligence Knowledge Graph Model Description Open-CyKG is a framework that is constructed using an attenti

Injy Sarhan 34 Jan 05, 2023
Mosaic of Object-centric Images as Scene-centric Images (MosaicOS) for long-tailed object detection and instance segmentation.

MosaicOS Mosaic of Object-centric Images as Scene-centric Images (MosaicOS) for long-tailed object detection and instance segmentation. Introduction M

Cheng Zhang 27 Oct 12, 2022
Research on controller area network Intrusion Detection Systems

Group members information Member 1: Lixue Liang Member 2: Yuet Lee Chan Member 3: Xinruo Zhang Member 4: Yifei Han User Manual Generate Attack Packets

Roche 4 Aug 30, 2022
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2020

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2020

Phillip Lippe 1.1k Jan 07, 2023
A library for answering questions using data you cannot see

A library for computing on data you do not own and cannot see PySyft is a Python library for secure and private Deep Learning. PySyft decouples privat

OpenMined 8.5k Jan 02, 2023
Multi-Stage Episodic Control for Strategic Exploration in Text Games

XTX: eXploit - Then - eXplore Requirements First clone this repo using git clone https://github.com/princeton-nlp/XTX.git Please create two conda envi

Princeton Natural Language Processing 9 May 24, 2022
Plato: A New Framework for Federated Learning Research

a new software framework to facilitate scalable federated learning research.

System <a href=[email protected] Lab"> 192 Jan 05, 2023
Code for Two-stage Identifier: "Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition"

Code for Two-stage Identifier: "Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition", accepted at ACL 2021. For details of the model and experiments, please see our paper.

tricktreat 87 Dec 16, 2022
Can we learn gradients by Hamiltonian Neural Networks?

Can we learn gradients by Hamiltonian Neural Networks? This project was carried out as part of the Optimization for Machine Learning course (CS-439) a

2 Aug 22, 2022
Official implementation of "Open-set Label Noise Can Improve Robustness Against Inherent Label Noise" (NeurIPS 2021)

Open-set Label Noise Can Improve Robustness Against Inherent Label Noise NeurIPS 2021: This repository is the official implementation of ODNL. Require

Hongxin Wei 12 Dec 07, 2022
Code for 'Single Image 3D Shape Retrieval via Cross-Modal Instance and Category Contrastive Learning', ICCV 2021

CMIC-Retrieval Code for Single Image 3D Shape Retrieval via Cross-Modal Instance and Category Contrastive Learning. ICCV 2021. Introduction In this wo

42 Nov 17, 2022
Pytorch Implementations of large number classical backbone CNNs, data enhancement, torch loss, attention, visualization and some common algorithms.

Torch-template-for-deep-learning Pytorch implementations of some **classical backbone CNNs, data enhancement, torch loss, attention, visualization and

Li Shengyan 270 Dec 31, 2022
Source code for PairNorm (ICLR 2020)

PairNorm Official pytorch source code for PairNorm paper (ICLR 2020) This code requires pytorch_geometric=1.3.2 usage For SGC, we use original PairNo

62 Dec 08, 2022
Pyeventbus: a publish/subscribe event bus

pyeventbus pyeventbus is a publish/subscribe event bus for Python 2.7. simplifies the communication between python classes decouples event senders and

15 Apr 21, 2022
PyTorch Language Model for 1-Billion Word (LM1B / GBW) Dataset

PyTorch Large-Scale Language Model A Large-Scale PyTorch Language Model trained on the 1-Billion Word (LM1B) / (GBW) dataset Latest Results 39.98 Perp

Ryan Spring 114 Nov 04, 2022