import tensorflow as tf

            shape=[num_filter],
            initializer=tf.constant_initializer(0.0))

        H = tf.nn.bias_add(
            name='H',
            value=conv,
            bias=b)
        
        # Apply nonlinearity
        H = tf.nn.relu(H, name="relu")
        
        # max pool
        pooled = tf.nn.max_pool(H,
                 ksize=[1, sequence_length - filter_size + 1, 1, 1],
                 strides=[1, 1, 1, 1],
                 padding='VALID',
                 name="pool")
        
