import tensorflow as tf

                            stddev=np.sqrt(1.0 / (width * char_embed_dim))
                        )
                    w = tf.get_variable(
                        "W_cnn_%s" % i,
                        [1, width, char_embed_dim, num],
                        initializer=w_init,
                        dtype=DTYPE)
                    b = tf.get_variable(
                        "b_cnn_%s" % i, [num], dtype=DTYPE,
                        initializer=tf.constant_initializer(0.0))

                    conv = tf.nn.conv2d(
                            inp, w,
                            strides=[1, 1, 1, 1],
                            padding="VALID") + b
                    # now max pool
                    conv = tf.nn.max_pool(
                            conv, [1, 1, max_chars-width+1, 1],
