CNNx = tf.nn.embedding_lookup(emb_mat, cnnx) [N, M, L, W, dc]

filter_sizes = [100]
heights = [5]
outs = []
for filter_size, height in zip(filter_sizes, heights):
    num_channels = 3
    filter_ = [1, height, num_channels, filter_size]
    strides = [1, 1, 1, 1]

    xxc = tf.nn.conv2d(Acx, filter_, strides, "VALID")  # [N*M, L, W/stride, d]
    out = tf.reduce_max(tf.nn.relu(xxc), 2)  # [-1, L, d]
    outs.append(xxc)

concat_out = tf.concat(2, outs)
xx = tf.reshape(concat_out, [-1, M, L, coz])

Ax = tf.nn.embedding_lookup(emb_mat, x)
xx = tf.concat(3, [xx, Ax])  # [N, M, L, di]