def test_incompatible_output_dimensions(self):
"""Compares to the scikit-learn RandomForestRegressor classifier.
"""
# create dataset with 4 outputs
X = np.random.rand(10, 20)
y = np.random.randint(low=0, high=3, size=(10, 4))
# create a model with 2 outputs
def build_fn_clf():
"""Builds a Sequential based classifier."""
model = keras.models.Sequential()
model.add(keras.layers.Dense(20, input_shape=(20,)))
model.add(keras.layers.Activation("relu"))
model.add(keras.layers.Dense(np.unique(y).size))
model.add(keras.layers.Activation("softmax"))
model.compile(
optimizer="sgd",
loss="categorical_crossentropy",
metrics=["accuracy"],
)
return model
clf = wrappers.KerasClassifier(build_fn=build_fn_clf)
with pytest.raises(RuntimeError):
clf.fit(X, y)
def test_classify_build_fn(self):
clf = wrappers.KerasClassifier(
build_fn=build_fn_clf,
hidden_dim=HIDDEN_DIM,
batch_size=BATCH_SIZE,
epochs=EPOCHS,
)
self.check_sample_weights_work(clf)
def test_pprint(self):
clf = wrappers.KerasClassifier(
build_fn=build_fn_clf,
hidden_dim=HIDDEN_DIM,
batch_size=BATCH_SIZE,
epochs=EPOCHS,
)
print(clf)
def test_classify_build_fn(self):
"""Tests a classification task for errors."""
clf = wrappers.KerasClassifier(
build_fn=build_fn_clf,
hidden_dim=HIDDEN_DIM,
batch_size=BATCH_SIZE,
epochs=EPOCHS,
)
assert_classification_works(clf)
def test_classify_class_build_fn(self):
"""Tests for errors using a class implementing __call__."""
class ClassBuildFnClf:
def __call__(self, hidden_dim):
return build_fn_clf(hidden_dim)
clf = wrappers.KerasClassifier(
build_fn=ClassBuildFnClf(),
hidden_dim=HIDDEN_DIM,
batch_size=BATCH_SIZE,
epochs=EPOCHS,
)
assert_classification_works(clf)
def test_classify_build_fn(self):
"""Tests a classification task for errors."""
clf = wrappers.KerasClassifier(
build_fn=build_fn_clf,
hidden_dim=HIDDEN_DIM,
batch_size=BATCH_SIZE,
epochs=EPOCHS,
)
X = np.random.rand(10, 20)
with pytest.raises(NotFittedError):
clf.predict(X)
with pytest.raises(NotFittedError):
clf.predict_proba(X)
def test_invalid_build_fn(self):
clf = wrappers.KerasClassifier(build_fn="invalid")
with pytest.raises(TypeError):
clf.fit(np.array([[0]]), np.array([0]))