def test_fdsrnn_lstm_fit():
X = np.random.standard_normal((13, 5, 4)).astype(theano.config.floatX)
Z = np.random.standard_normal((13, 5, 3)).astype(theano.config.floatX)
W = np.random.standard_normal((13, 5, 3)).astype(theano.config.floatX)
X, Z, W = theano_floatx(X, Z, W)
rnn = SupervisedFastDropoutRnn(4, [10], 3, hidden_transfers=['lstm'],
max_iter=2)
rnn.mode = 'FAST_COMPILE'
rnn.fit(X, Z)
def test_fdsrnn_lstm_fit():
X = np.random.standard_normal((13, 5, 4)).astype(theano.config.floatX)
Z = np.random.standard_normal((13, 5, 3)).astype(theano.config.floatX)
W = np.random.standard_normal((13, 5, 3)).astype(theano.config.floatX)
X, Z, W = theano_floatx(X, Z, W)
rnn = SupervisedFastDropoutRnn(4, [10],
3,
hidden_transfers=['lstm'],
max_iter=2)
rnn.mode = 'FAST_COMPILE'
rnn.fit(X, Z)
