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
Self-Supervised CNN-GCN Autoencoder

GCNDepth Self-Supervised CNN-GCN Autoencoder GCNDepth: Self-supervised monocular depth estimation based on graph convolutional network To be published

53 Dec 14, 2022
Implementation for the paper 'YOLO-ReT: Towards High Accuracy Real-time Object Detection on Edge GPUs'

YOLO-ReT This is the original implementation of the paper: YOLO-ReT: Towards High Accuracy Real-time Object Detection on Edge GPUs. Prakhar Ganesh, Ya

69 Oct 19, 2022
the code used for the preprint Embedding-based Instance Segmentation of Microscopy Images.

EmbedSeg Introduction This repository hosts the version of the code used for the preprint Embedding-based Instance Segmentation of Microscopy Images.

JugLab 88 Dec 25, 2022
TensorFlow for Raspberry Pi

TensorFlow on Raspberry Pi It's officially supported! As of TensorFlow 1.9, Python wheels for TensorFlow are being officially supported. As such, this

Sam Abrahams 2.2k Dec 16, 2022
Using VapourSynth with super resolution models and speeding them up with TensorRT.

VSGAN-tensorrt-docker Using image super resolution models with vapoursynth and speeding them up with TensorRT. Using NVIDIA/Torch-TensorRT combined wi

111 Jan 05, 2023
A Jupyter notebook to play with NVIDIA's StyleGAN3 and OpenAI's CLIP for a text-based guided image generation.

A Jupyter notebook to play with NVIDIA's StyleGAN3 and OpenAI's CLIP for a text-based guided image generation.

Eugenio Herrera 175 Dec 29, 2022
PyG (PyTorch Geometric) - A library built upon PyTorch to easily write and train Graph Neural Networks (GNNs)

PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.

PyG 16.5k Jan 08, 2023
codes for "Scheduled Sampling Based on Decoding Steps for Neural Machine Translation" (long paper of EMNLP-2022)

Scheduled Sampling Based on Decoding Steps for Neural Machine Translation (EMNLP-2021 main conference) Contents Overview Background Quick to Use Furth

Adaxry 13 Jul 25, 2022
Official Implementation of HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation

HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation by Lukas Hoyer, Dengxin Dai, and Luc Van Gool [Arxiv] [Paper] Overview Unsup

Lukas Hoyer 149 Dec 28, 2022
A collection of awesome resources image-to-image translation.

awesome image-to-image translation A collection of resources on image-to-image translation. Contributing If you think I have missed out on something (

876 Dec 28, 2022
The official code of "SCROLLS: Standardized CompaRison Over Long Language Sequences".

SCROLLS This repository contains the official code of the paper: "SCROLLS: Standardized CompaRison Over Long Language Sequences". Links Official Websi

TAU NLP Group 39 Dec 23, 2022
This repo is duplication of jwyang/faster-rcnn.pytorch

Faster RCNN Pytorch This repo is duplication of jwyang/faster-rcnn.pytorch C/C++ code are removed and easier to study. Python 3.8.5 Ubuntu 20.04.1 LTS

Kim Jihwan 1 Jan 14, 2022
Text to image synthesis using thought vectors

Text To Image Synthesis Using Thought Vectors This is an experimental tensorflow implementation of synthesizing images from captions using Skip Though

Paarth Neekhara 2.1k Jan 05, 2023
Differential rendering based motion capture blender project.

TraceArmature Summary TraceArmature is currently a set of python scripts that allow for high fidelity motion capture through the use of AI pose estima

William Rodriguez 4 May 27, 2022
Ensembling Off-the-shelf Models for GAN Training

Vision-aided GAN video (3m) | website | paper Can the collective knowledge from a large bank of pretrained vision models be leveraged to improve GAN t

345 Dec 28, 2022
Chunkmogrify: Real image inversion via Segments

Chunkmogrify: Real image inversion via Segments Teaser video with live editing sessions can be found here This code demonstrates the ideas discussed i

David Futschik 112 Jan 04, 2023
Sub-tomogram-Detection - Deep learning based model for Cyro ET Sub-tomogram-Detection

Deep learning based model for Cyro ET Sub-tomogram-Detection High degree of stru

Siddhant Kumar 2 Feb 04, 2022
《Unsupervised 3D Human Pose Representation with Viewpoint and Pose Disentanglement》(ECCV 2020) GitHub: [fig9]

Unsupervised 3D Human Pose Representation [Paper] The implementation of our paper Unsupervised 3D Human Pose Representation with Viewpoint and Pose Di

42 Nov 24, 2022
Deep generative models of 3D grids for structure-based drug discovery

What is liGAN? liGAN is a research codebase for training and evaluating deep generative models for de novo drug design based on 3D atomic density grid

Matt Ragoza 152 Jan 03, 2023