def test_reg_build_fn(self):
clf = wrappers.KerasRegressor(
build_fn=build_fn_reg,
hidden_dim=HIDDEN_DIM,
batch_size=BATCH_SIZE,
epochs=EPOCHS,
)
self.check_sample_weights_work(clf)
def test_regression_build_fn(self):
"""Tests for errors using KerasRegressor."""
reg = wrappers.KerasRegressor(
build_fn=build_fn_reg,
hidden_dim=HIDDEN_DIM,
batch_size=BATCH_SIZE,
epochs=EPOCHS,
)
assert_regression_works(reg)
def test_regression_build_fn(self):
"""Tests for errors using KerasRegressor."""
reg = wrappers.KerasRegressor(
build_fn=build_fn_reg,
hidden_dim=HIDDEN_DIM,
batch_size=BATCH_SIZE,
epochs=EPOCHS,
)
# create dataset
X = np.random.rand(10, 20)
with pytest.raises(NotFittedError):
reg.predict(X)
def test_regression_class_build_fn(self):
"""Tests for errors using KerasRegressor implementing __call__."""
class ClassBuildFnReg:
def __call__(self, hidden_dim):
return build_fn_reg(hidden_dim)
reg = wrappers.KerasRegressor(
build_fn=ClassBuildFnReg(),
hidden_dim=HIDDEN_DIM,
batch_size=BATCH_SIZE,
epochs=EPOCHS,
)
assert_regression_works(reg)
