d3196bee4759550bc2e944a945881013157669ef,examples/tensorboard_simple.py,,,#,35

Before Change

param_distributions = dict()  // type: Dict[str, Any]
param_distributions["NUM_UNITS"] = ("int_uniform", (16, 32))
param_distributions["DROPOUT_RATE"] = ("uniform", (0.1, 0.2))
param_distributions["OPTIMIZER"] = ("categorical", (["sgd", "adam"],))


def objective(trial: "optuna.trial.Trial") -> float:

After Change

tensorboard_callback = TensorBoardCallback("logs/", param_distributions, metric_name="accuracy")

study = optuna.create_study(direction="maximize")
study.optimize(objective, n_trials=10, timeout=600, callbacks=[tensorboard_callback])

Instances