Get started tuning hyperparameters with W&B quickly

sweeps_quickstart.py

import wandb

# 1: Define objective/training function
def objective(config):
    score = config.x ** 3 + config.y
    return score

def main():
    wandb.init(project='my-first-sweep')
    score = objective(wandb.config)
    wandb.log({'score': score})

# 2: Define the search space
sweep_configuration = {
    'method': 'random',
    'metric': {'goal': 'minimize', 'name': 'score'},
    'parameters': 
    {
        'x': {'max': 0.1, 'min': 0.01},
        'y': {'values': [1, 3, 7]},
     }
}

# 3: Start the sweep
sweep_id = wandb.sweep(sweep=sweep_configuration, project='my-first-sweep')
wandb.agent(sweep_id, function=main, count=10)