Python tflearn.embedding() Examples

The following are 2 code examples of tflearn.embedding(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module tflearn , or try the search function .
Example #1
Source File: sentiment.py    From TaobaoAnalysis with MIT License 5 votes vote down vote up 
def _create_model(self):
        reset_default_graph()
        net = input_data([None, SEQUENCE_LEN])
        net = embedding(net, input_dim=len(self._vocab.vocabulary_),
                        output_dim=WORD_FEATURE_DIM)
        net = lstm(net, DOC_FEATURE_DIM, dropout=0.8)
        net = fully_connected(net, 2, activation='softmax')
        net = regression(net, optimizer='adam', learning_rate=0.001,
                         loss='categorical_crossentropy')
        return DNN(net)
Example #2
Source File: test_layers.py    From FRU with MIT License 5 votes vote down vote up 
def test_recurrent_layers(self):

        X = [[1, 3, 5, 7], [2, 4, 8, 10], [1, 5, 9, 11], [2, 6, 8, 0]]
        Y = [[0., 1.], [1., 0.], [0., 1.], [1., 0.]]

        with tf.Graph().as_default():
            g = tflearn.input_data(shape=[None, 4])
            g = tflearn.embedding(g, input_dim=12, output_dim=4)
            g = tflearn.lstm(g, 6)
            g = tflearn.fully_connected(g, 2, activation='softmax')
            g = tflearn.regression(g, optimizer='sgd', learning_rate=1.)

            m = tflearn.DNN(g)
            m.fit(X, Y, n_epoch=300, snapshot_epoch=False)
            self.assertGreater(m.predict([[5, 9, 11, 1]])[0][1], 0.9)