Cloud/CLI trainer

pinn_train is a command line utility to train a model. The program is meant to work with the Google Cloud AI platform, but it should also run well on local machines.

The trainer effectively runs train_and_evaluate with the given dataset. To use the trainer, both training data and evaluation data must be prepared as a tfrecord format. Currently, only training potentials is supported. To see the available options, run pinn_train --help

Example usage of pinn_train on a local machine:

pinn_trian --model-dir=my_model --params=params.yml \
           --train-data=train.yml --eval-data=test.yml \
           --max-steps=1e6 --eval-steps=100 \
           --cache-data=True

Example usage of pinn_train on Google Cloud:

It is recommanded to use our docker image. Since we do not serve it on Google Container Registery, you’ll need to build one yourself (suppose you have an active Gclound project):

gcloud auth configure-docker
docker pull yqshao/pinn:dev
docker tag yqshao/pinn:dev gcr.io/my-proj/pinn:cpu
docker push gcr.io/my-proj/pinn:cpu

To submit a job on Gcloud:

gcloud ai-platform jobs submit training my_job_0 \
       --region europe-west1 --master-image-uri gcr.io/my-proj/pinn:cpu \
       -- \
       --model-dir=gs://my-bucket/models/my_model_0 \
       --params-file=gs://my-bucket/models/params.yml \
       --train-data=gs://my-bucket/data/train.yml \
       --eval-data=gs://my-bucket/data/test.yml \
       --train-steps=1000 --cache-data=True