def test_usrnn_fit(): raise SkipTest() X = np.random.standard_normal((10, 5, 2)).astype(theano.config.floatX) X, = theano_floatx(X) rnn = UnsupervisedRnn(2, [10], 3, hidden_transfers=['tanh'], loss=lambda x: T.log(x), max_iter=10) rnn.fit(X)
def test_usrnn_fit(): X = np.random.standard_normal((10, 5, 2)).astype(theano.config.floatX) rnn = UnsupervisedRnn(2, 10, 3, loss=lambda x: T.log(x), max_iter=10) rnn.fit(X)
def test_usrnn_fit(): X = np.random.standard_normal((10, 5, 2)) rnn = UnsupervisedRnn(2, 10, 3, loss=lambda x: T.log(x), max_iter=10) rnn.fit(X)