test_keras2_numeric.py 文件源码

def test_lstm_td(self):
        np.random.seed(1988)
        input_dim = 2
        input_length = 4
        num_channels = 3

        # Define a model
        model = Sequential()
        model.add(SimpleRNN(num_channels, return_sequences=True, 
                input_shape=(input_length, input_dim),))
        model.add(TimeDistributed(Dense(5)))

        # Set some random weights
        model.set_weights([np.random.rand(*w.shape)*0.2 - 0.1 for w in \
                model.get_weights()])

        # Test the keras model
        self._test_keras_model(model, input_blob = 'data', 
                output_blob = 'output')


    # Making sure that giant channel sizes get handled correctly