Example create Optuna study

import subprocess

def create_study(study_name, dataset, trial_job_cnt, trials_per_job, api_key, storage, sampler):
    
    study = optuna.create_study(study_name=study_name,storage=storage, sampler=sampler, direction="maximize")
    
    # Tell Optuna to start with our default config settings

    study.enqueue_trial(
        {
        "vocab_size": config['models'][0]['synthetics']['params']['vocab_size'],
        "reset_states": config['models'][0]['synthetics']['params']['reset_states'],
        "rnn_units": config['models'][0]['synthetics']['params']['rnn_units'],
        "learning_rate": config['models'][0]['synthetics']['params']['learning_rate'],
        "gen_temp": config['models'][0]['synthetics']['params']['gen_temp'],
        "dropout_rate": config['models'][0]['synthetics']['params']['dropout_rate'],
        }
    )
    
    # We will run a total of "trial_cnt" trials with "trial_job_cnt" number of processes running in parallel
    
    trial_cnt = str(trials_per_job)
    for i in range(trial_job_cnt):
        mytrial = subprocess.Popen(["python", "Optuna_Trials.py", study_name, trial_cnt, dataset, api_key, storage])
    
    return study