def test_tf_shallow_neural_classifier(XOR):
"""Just makes sure that this code will run; it doesn't check that
it is creating good models.
"""
X, y = XOR
model = tf_shallow_neural_classifier.TfShallowNeuralClassifier(
hidden_dim=4, hidden_activation=tf.nn.tanh, max_iter=100, eta=0.01)
model.fit(X, y)
model.predict(X)
model.predict_proba(X)
}
],
[
torch_autoencoder.TorchAutoencoder(
hidden_dim=5, hidden_activation=nn.ReLU(), max_iter=1,
eta=1.0), {
'hidden_dim': 10,
'hidden_activation': nn.ReLU(),
'max_iter': 10,
'eta': 0.1
}
],
[
tf_shallow_neural_classifier.TfShallowNeuralClassifier(
hidden_dim=5,
hidden_activation=tf.nn.tanh,
max_iter=1,
eta=1.0), {
'hidden_dim': 10,
'hidden_activation': tf.nn.relu,
'max_iter': 10,
'eta': 0.1
}
],
[
tf_autoencoder.TfAutoencoder(hidden_dim=5,
hidden_activation=tf.nn.tanh,
max_iter=1,
eta=1.0), {
'hidden_dim': 10,
'hidden_activation': tf.nn.relu,