Fit model, dump to S3 via s3fs

fit_dump_model_to_s3fs.py

import s3fs
import pickle
import json
import numpy as np

BUCKET_NAME = "my-bucket"

# definitions, keras/tf/... imports...

if __name__ == "__main__":
  s3 = s3fs.S3FileSystem(anon=False) # mount
  model_options = { "name": "",
    "comment": "trained on half the dataset",
      "params": {
      "n_trees": 4
    }}

  json.dump(model_options, s3.open(f"{BUCKET_NAME}/options_{model_options['name'] + str(np.random.randint(10000))}.json",'w'))

  model = generate_baseline(model_options["params"]) # generate some base line model with whatever option we want to use.
  model.fit(X,y)
  pickle.dump(model, s3.open(f"{BUCKET_NAME}/model_{model_options['name'] + str(np.random.randint(10000))}.pkl",'w'))