convert_to_valohai.py

# import valohai_yaml
import sys

import pyaml
import yaml
import pathlib

from valohai_yaml.objs import Step, Parameter, Config

params = []

for yaml_fn in pathlib.Path("yaml_files").glob("*.yaml"):
    with open(yaml_fn) as f:
        data = yaml.safe_load(f)
    for key, value in data.items():
        if isinstance(value, int):
            params.append(Parameter(name=key, type="integer", default=value, multiple_separator='\',\''))
        elif isinstance(value, float):
            params.append(Parameter(name=key, type="float", default=value, multiple_separator='\',\''))
        elif isinstance(value, str):
            params.append(Parameter(name=key, type="string", default=value, multiple_separator='\',\''))
        elif isinstance(value, bool):
            params.append(Parameter(name=key, type="flag", default=value))
        elif isinstance(value, list):
            if not value:
                params.append(Parameter(name=key, type="string", default="", multiple_separator='\',\'', multiple="separate"))
            else:
                params.append(Parameter(name=key, type="string", default=','.join([str(i) for i in value]), multiple_separator='\',\'', multiple="separate"))
        else:
            print(f'Skipping Key {key} Value: {value}')

step = Step(
    name="test",
    parameters=params,
    image="python:3.9",
    command="- python tf_train_model_template.py",
)

config = Config(steps=[step])

with open(r'valohai.yaml', 'w') as file:
    pyaml.dump(config.serialize(), file)