def test_tf_autoencoder(pandas):
"""Just makes sure that this code will run; it doesn't check that
it is creating good models.
"""
X = utils.randmatrix(20, 50)
if pandas:
X = pd.DataFrame(X)
ae = tf_autoencoder.TfAutoencoder(hidden_dim=5, max_iter=100)
H = ae.fit(X)
ae.predict(X)
H_is_pandas = isinstance(H, pd.DataFrame)
assert H_is_pandas == pandas
}
],
[
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,
'max_iter': 10,
'eta': 0.1
}
]
])
def test_parameter_setting(model, params):
model.set_params(**params)
for p, val in params.items():
assert getattr(model, p) == val