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word_language_model
word_language_model
 
 
README.md
README.md
 
 
__init__.py
__init__.py
 
 
cluster.yaml
cluster.yaml
 
 
grid_search_space.py
grid_search_space.py
 
 
test_ddp.py
test_ddp.py
 
 
tune_asha_cifar.py
tune_asha_cifar.py
 
 
tune_asha_dcgan.py
tune_asha_dcgan.py
 
 
tune_asha_mnist.py
tune_asha_mnist.py
 
 
tune_asha_para_cifar.py
tune_asha_para_cifar.py
 
 
tune_asha_para_mnist.py
tune_asha_para_mnist.py
 
 
tune_asha_para_mnist_upgrade.py
tune_asha_para_mnist_upgrade.py
 
 
tune_asha_wlm.py
tune_asha_wlm.py
 
 
tune_bohb_cifar.py
tune_bohb_cifar.py
 
 
tune_bohb_dcgan.py
tune_bohb_dcgan.py
 
 
tune_bohb_mnist.py
tune_bohb_mnist.py
 
 
tune_bohb_wlm.py
tune_bohb_wlm.py
 
 
tune_fluid_dcgan.py
tune_fluid_dcgan.py
 
 
tune_fluid_mnist.py
tune_fluid_mnist.py
 
 
tune_fluid_wlm.py
tune_fluid_wlm.py
 
 
tune_grid_cifar.py
tune_grid_cifar.py
 
 
tune_grid_dcgan.py
tune_grid_dcgan.py
 
 
tune_grid_mnist.py
tune_grid_mnist.py
 
 
tune_grid_wlm.py
tune_grid_wlm.py
 
 
tune_hb_cifar.py
tune_hb_cifar.py
 
 
tune_hb_dcgan.py
tune_hb_dcgan.py
 
 
tune_hb_mnist.py
tune_hb_mnist.py
 
 
tune_hb_wlm.py
tune_hb_wlm.py
 
 
tune_pbt_cifar.py
tune_pbt_cifar.py
 
 
tune_pbt_dcgan.py
tune_pbt_dcgan.py
 
 
tune_pbt_mnist.py
tune_pbt_mnist.py
 
 
tune_pbt_wlm.py
tune_pbt_wlm.py
 
 
tune_syncbohb_cifar.py
tune_syncbohb_cifar.py
 
 
tune_syncbohb_dcgan.py
tune_syncbohb_dcgan.py
 
 
tune_syncbohb_mnist.py
tune_syncbohb_mnist.py
 
 
tune_syncbohb_wlm.py
tune_syncbohb_wlm.py
 
 

README.md

Experiments in Paper

Clone the Repo

To run experiments, it is necessary to clone this repo, instad of installing fluid from PyPI.

fluid uses poetry to manage its dependencies, so poetry has to be installed first.

curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python -
git clone https://github.com/SymbioticLab/fluid
cd fluid
poetry install --extras "exp"
poetry shell

The last command spawns a new shell within the virtual environment just created with all dependencies installed.

Setup a Minimal Ray Cluster

cluster.yaml provides an example Ray cluster config file that you can use as the starting point to bring up a Ray cluster.

Run Individual Experiments

Each tune_*.py file in this directory is an experiment that can run individualy.

To run them, first ensure the Ray cluster can be connected, then run python -m workloads.tune_asha_cifar from the root directory of the repo.

After it finishes, some statistical results will be saved in trail_dataframe.csv.