对应 tensorflow 1.15版本
log_dir = "./logdir"
metadata_path = os.path.join(log_dir, 'metadata.csv')
names = ["苹果", "香蕉"]
embs = [[1.0, 2.0, 0.1, 0.4], [1.0, 1.0, 0.1, 0.4]]
with open(metadata_path, "w") as f:
for name in names:
f.write("{}\n".format(name))
embedding = tf.Variable(embs, dtype=tf.float32)
ckpt = tf.train.Checkpoint(embedding=embedding)
with tf.Session() as sess:
tf.global_variables_initializer().run()
ckpt.save(os.path.join(log_dir, "embedding.ckpt"))
from tensorboard.plugins import projector
config = projector.ProjectorConfig()
cfg_emb = config.embeddings.add()
cfg_emb.tensor_name = "embedding/.ATTRIBUTES/VARIABLE_VALUE"
cfg_emb.metadata_path = 'metadata.csv'
projector.visualize_embeddings(tf.summary.FileWriter(log_dir), config)
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