def test_fd_srnn_iter_fit():
X = np.random.standard_normal((10, 5, 2)).astype(theano.config.floatX)
Z = np.random.standard_normal((10, 5, 3)).astype(theano.config.floatX)
X, Z = theano_floatx(X, Z)
rnn = SupervisedFastDropoutRnn(2, [10], 3, hidden_transfers=['rectifier'], max_iter=10)
for i, info in enumerate(rnn.iter_fit(X, Z)):
if i >= 10:
break
rnn = SupervisedFastDropoutRnn(
2, [10, 20], 3, hidden_transfers=['rectifier', 'tanh'],
skip_to_out=True, max_iter=10)
for i, info in enumerate(rnn.iter_fit(X, Z)):
if i >= 10:
break
def test_fd_srnn_iter_fit():
raise SkipTest()
X = np.random.standard_normal((10, 5, 2)).astype(theano.config.floatX)
Z = np.random.standard_normal((10, 5, 3)).astype(theano.config.floatX)
X, Z = theano_floatx(X, Z)
rnn = SupervisedFastDropoutRnn(2, [10], 3, hidden_transfers=['rectifier'], max_iter=10)
for i, info in enumerate(rnn.iter_fit(X, Z)):
if i >= 10:
break
rnn = SupervisedFastDropoutRnn(
2, [10, 20], 3, hidden_transfers=['rectifier', 'tanh'],
skip_to_out=True, max_iter=10)
for i, info in enumerate(rnn.iter_fit(X, Z)):
if i >= 10:
break
def test_fd_srnn_iter_fit():
X = np.random.standard_normal((10, 5, 2)).astype(theano.config.floatX)
Z = np.random.standard_normal((10, 5, 3)).astype(theano.config.floatX)
rnn = SupervisedFastDropoutRnn(2, [10], 3, hidden_transfer='rectifier', max_iter=10)
for i, info in enumerate(rnn.iter_fit(X, Z)):
if i >= 10:
break
def test_fd_srnn_iter_fit():
X = np.random.standard_normal((10, 5, 2)).astype(theano.config.floatX)
Z = np.random.standard_normal((10, 5, 3)).astype(theano.config.floatX)
rnn = SupervisedFastDropoutRnn(2, [10],
3,
hidden_transfer='rectifier',
max_iter=10)
for i, info in enumerate(rnn.iter_fit(X, Z)):
if i >= 10:
break
