def build_simple_model(self):
    'Build a simple model for test\n        Returns:\n            DNN, [ (input layer name, input placeholder, input data) ], Target data\n        '
    (inputPlaceholder1, inputPlaceholder2) = (tf.placeholder(tf.float32, (1, 1), name='input1'), tf.placeholder(tf.float32, (1, 1), name='input2'))
    input1 = zqtflearn.input_data(placeholder=inputPlaceholder1)
    input2 = zqtflearn.input_data(placeholder=inputPlaceholder2)
    network = zqtflearn.merge([input1, input2], 'sum')
    network = zqtflearn.reshape(network, (1, 1))
    network = zqtflearn.fully_connected(network, 1)
    network = zqtflearn.regression(network)
    return (zqtflearn.DNN(network), [('input1:0', inputPlaceholder1, self.INPUT_DATA_1), ('input2:0', inputPlaceholder2, self.INPUT_DATA_2)], self.TARGET)
Build a simple model for test
Returns:
    DNN, [ (input layer name, input placeholder, input data) ], Target data
def build_simple_model(self):
    'Build a simple model for test\n        Returns:\n            DNN, [ (input layer name, input placeholder, input data) ], Target data\n        '
    (inputPlaceholder1, inputPlaceholder2) = (tf.placeholder(tf.float32, (1, 1), name='input1'), tf.placeholder(tf.float32, (1, 1), name='input2'))
    input1 = zqtflearn.input_data(placeholder=inputPlaceholder1)
    input2 = zqtflearn.input_data(placeholder=inputPlaceholder2)
    network = zqtflearn.merge([input1, input2], 'sum')
    network = zqtflearn.reshape(network, (1, 1))
    network = zqtflearn.fully_connected(network, 1)
    network = zqtflearn.regression(network)
    return (zqtflearn.DNN(network), [('input1:0', inputPlaceholder1, self.INPUT_DATA_1), ('input2:0', inputPlaceholder2, self.INPUT_DATA_2)], self.TARGET)