def test_warm_start():
"""Test the warm start parameter."""
# Load data
data = fetch_california_housing()
X, y = data.data[:100], data.target[:100]
# Initial fit
estimator = KerasRegressor(
model=dynamic_regressor,
model__hidden_layer_sizes=(100,),
)
estimator.fit(X, y)
model = estimator.model_
# With warm start, successive calls to fit
# should NOT create a new model
estimator.set_params(warm_start=True)
estimator.fit(X, y)
assert model is estimator.model_
# Without warm start, each call to fit
# should create a new model instance
estimator.set_params(warm_start=False)
for _ in range(3):
estimator.fit(X, y)
assert model is not estimator.model_
model = estimator.model_
def test_current_epoch_property(self, warm_start, epochs_prefix):
"""Test the public current_epoch property
that tracks the overall training epochs.
The warm_start parameter should have
NO impact on this behavior.
The prefix should NOT have any impact on
behavior. It is tested because the epochs
param has special handling within param routing.
"""
data = load_boston()
X, y = data.data[:10], data.target[:10]
epochs = 2
partial_fit_iter = 3
estimator = KerasRegressor(
model=dynamic_regressor,
loss=KerasRegressor.r_squared,
model__hidden_layer_sizes=[],
warm_start=warm_start,
)
estimator.set_params(**{epochs_prefix + "epochs": epochs})
# Check that each partial_fit call trains for 1 epoch
for k in range(1, partial_fit_iter):
estimator.partial_fit(X, y)
assert estimator.current_epoch == k
# Check that fit calls still train for the number of
# epochs specified in the constructor
estimator.fit(X, y)
assert estimator.current_epoch == epochs
# partial_fit is able to resume from a non-zero epoch
estimator.partial_fit(X, y)
assert estimator.current_epoch == epochs + 1
