import tensorflow as tf

        print("-" * 20)

        self.layers = []

        # Temp(First) Conv Layer
        with tf.variable_scope("temp_conv") as scope: 
            filter_shape = [3, embedding_size, 4, 64]
            W = tf.get_variable(name='W_1', shape=filter_shape, 
                initializer=he_normal,
                regularizer=regularizer)
            paddings = [[0, 0], [1, 1], [0, 0], [0, 0]]
            cnn_inputs = tf.pad(cnn_inputs, paddings, "CONSTANT")
            #print("cnn_inputs shape:", cnn_inputs.shape)
            inputs = tf.nn.conv2d(cnn_inputs, W, strides=[1, 1, 1, 1], padding="VALID", name="first_conv")
            inputs = tf.layers.batch_normalization(inputs, axis=-1, training=self.is_training)
            inputs = tf.nn.relu(inputs, name="first_relu")
            #print("temp cnn output shape:", inputs.shape)
            inputs = tf.squeeze(inputs, axis=2)
            #print("squeeze shape", inputs.shape)
            #inputs = tf.nn.relu(inputs)
        print("Temp Conv", inputs.get_shape())
        self.layers.append(inputs)
