How to obtain value from GDBT Regressor?

General Discussion
#1

Hello, I have Regressor code from example

# Build the input function.
train_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(
    x={'x': x_train}, y=y_train,
    batch_size=batch_size, num_epochs=None, shuffle=True)
test_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(
    x={'x': x_test}, y=y_test,
    batch_size=batch_size, num_epochs=1, shuffle=False)
# GBDT Models from TF Estimator requires 'feature_column' data format.
feature_columns = [tf.feature_column.numeric_column(key='x', shape=(num_features,))]

gbdt_regressor = tf.estimator.BoostedTreesRegressor(
    n_batches_per_layer=num_batches_per_layer,
    feature_columns=feature_columns, 
    learning_rate=learning_rate, 
    n_trees=num_trees,
    max_depth=max_depth,
    l1_regularization=l1_regul, 
    l2_regularization=l2_regul
)

gbdt_regressor.train(train_input_fn, max_steps=max_steps)

gbdt_regressor.evaluate(test_input_fn)

Can someone advise me how to use the function to obtain value estimate from parameters? Whole example is here: TensorFlow-Examples/gradient_boosted_trees.ipynb at master · aymericdamien/TensorFlow-Examples · GitHub
Thank you