Node Pool Forecast Engine

Description

Forecast the demands of video conferences for performance, cost-efficiency

How to run

Install dependencies

# clone project
git clone https://github.com/transverse-dev/node-pool-forecast-engine
cd node-pool-forecast-engine

# [OPTIONAL] create conda environment
conda create -n myenv python=3.9
conda activate myenv

# install pytorch according to instructions
# https://pytorch.org/get-started/

# install requirements
pip install -r requirements.txt

Train model with default configuration

# train on CPU
python src/train.py trainer=cpu

# train on GPU
python src/train.py trainer=gpu

Train model with chosen experiment configuration from configs/experiment/

python src/train.py experiment=experiment_name.yaml

You can override any parameter from command line like this

python src/train.py trainer.max_epochs=20 datamodule.batch_size=64