Beispiel #1
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def test_slstm_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)
    rnn = SupervisedLstm(2, 10, 3, max_iter=10)
    for i, info in enumerate(rnn.iter_fit(X, Z)):
        if i >= 10:
            break
Beispiel #2
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def test_slstm_iter_fit():
    raise SkipTest()
    X = np.random.standard_normal((10, 5, 2))
    Z = np.random.standard_normal((10, 5, 3))
    rnn = SupervisedLstm(2, 10, 3, max_iter=10)
    for i, info in enumerate(rnn.iter_fit(X, Z)):
        if i >= 10:
            break
Beispiel #3
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def test_slstm():
    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)
    rnn = SupervisedLstm(2, 10, 3, max_iter=10)
    rnn.fit(X, Z)
Beispiel #4
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def test_slstm_predict():
    raise SkipTest()
    X = np.random.standard_normal((10, 5, 2))
    rnn = SupervisedLstm(2, 10, 3, max_iter=10)
    rnn.predict(X)
Beispiel #5
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def test_slstm():
    raise SkipTest()
    X = np.random.standard_normal((10, 5, 2))
    Z = np.random.standard_normal((10, 5, 3))
    rnn = SupervisedLstm(2, 10, 3, max_iter=10)
    rnn.fit(X, Z)
Beispiel #6
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def test_slstm_predict():
    raise SkipTest()
    X = np.random.standard_normal((10, 5, 2)).astype(theano.config.floatX)
    rnn = SupervisedLstm(2, 10, 3, max_iter=10)
    rnn.predict(X)