Embedding Projector: "Color by" drop-down not showing up on multi-column .tsv

Migrated from https://github.com/tensorflow/tensorflow/issues/9688

Describe the problem

Tensorboard does not display the Color By dropdown menu on multi-columnar data. Label by and search by displaying columns normally.

Source code / logs

Sample of metadata.tsv file:

Name	Genre
(Sandy) Alex G	Alternative/Indie Rock	
*NSYNC	Pop/Rock	
Acollective	Pop/Rock	
Ahmet Özhan	International	
Ahu	Club/Dance	
Alex Ferreira	Pop/Rock	
Alex Winston	Pop/Rock	
Ali Azimi	Pop/Rock	
Alphamama	Pop/Rock	
Amaryllis	International	
...
Yomo Toro	Latin
Youssou N'Dour	International
Zafra Negra	Latin
Zany	Electronic	
Zeki Müren	International
iSHi	Electronic	

Code to generate embeddings and metadata:

def list_to_tsv(filenames, metadata_dir):
    with open(os.path.join(metadata_dir,'metadata.tsv'), 'w') as tsvfile:
        writer = csv.writer(tsvfile, delimiter = "\t")
        for record in filenames:
            writer.writerow(record)

def save_down_tensors(tensor_dir, name_and_embedding):
    embeddings = [i[2] for i in name_and_embedding] 
    names = [[i[0],i[1]] for i in name_and_embedding]
    names.insert(0,['Name','Genre'])
    with tf.Session() as sess:
        embeddings_tf = tf.Variable(np.array(embeddings), name = "embeddings")
        tf.global_variables_initializer().run()
        # save the tensor down
        saver = tf.train.Saver(tf.global_variables())
        saver.save(sess, tensor_dir, 0)
        # associate metadata with the embedding
        summary_writer = tf.summary.FileWriter(tensor_dir)
        config = projector.ProjectorConfig()
        embedding = config.embeddings.add()
        embedding.tensor_name = embeddings_tf.name
        #save filenames to tsv
        list_to_tsv(names, metadata_dir)
        embedding.metadata_path = os.path.join(metadata_dir, "metadata.tsv")
        # save a configuration file that TensorBoard will read during startup.
        projector.visualize_embeddings(summary_writer, config)

[danhper]

The threshold is hard coded here: https://github.com/tensorflow/tensorboard/blob/master/tensorboard/plugins/projector/vz_projector/data-provider.ts#L21

[danhper]

I ran into the same issue. After taking a look at the code, it seems that the maximum number of unique values for a column to be used in color-by is 50. I tried to increase the threshold and run the projector on my data with ~100 unique values (10000 points non-evenly distributed with respect to the color-by filter) and did not run in any performance issue on an average laptop. What would need to be done to be able to increase this threshold?