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"""
plot_intermediate_values
========================
.. autofunction:: optuna.visualization.matplotlib.plot_intermediate_values
The following code snippet shows how to plot intermediate values.
"""
import optuna
def f(x):
return (x - 2) ** 2
def df(x):
return 2 * x - 4
def objective(trial):
lr = trial.suggest_float("lr", 1e-5, 1e-1, log=True)
x = 3
for step in range(128):
y = f(x)
trial.report(y, step=step)
if trial.should_prune():
raise optuna.TrialPruned()
gy = df(x)
x -= gy * lr
return y
sampler = optuna.samplers.TPESampler(seed=10)
study = optuna.create_study(sampler=sampler)
study.optimize(objective, n_trials=16)
optuna.visualization.matplotlib.plot_intermediate_values(study)
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