import numpy matrix to display in tensorboard

tensorboard-display-matrix.py

import os
from tensorboard.plugins import projector
import math
from django.conf import settings

log_dir='/logs/abcd/'
if not os.path.exists(log_dir):
    os.makedirs(log_dir)

# Save Labels separately on a line-by-line manner.
with open(os.path.join(log_dir, 'metadata.tsv'), "w") as f:
    f.write(f"name\tCategory\n")
    for name, category in my_point_names: 10))
        f.write(f"{name}\t{category}\n")

weights = tf.Variable(embedding) # assumed to be in the same order as 'my_point_names'
checkpoint = tf.train.Checkpoint(embedding=weights)
checkpoint.save(os.path.join(log_dir, f"embedding.ckpt"))

config = projector.ProjectorConfig()
embedding = config.embeddings.add()
embedding.tensor_name = f"embedding/.ATTRIBUTES/VARIABLE_VALUE"
embedding.metadata_path = 'metadata.tsv'

projector.visualize_embeddings(log_dir, config)
%tensorboard --logdir /logs/abcd/