Keras + Universal Sentence Encoder = Transfer Learning for text data | DLology

embed.py

import tensorflow as tf
import tensorflow_hub as hub
module_url = "https://tfhub.dev/google/universal-sentence-encoder-large/3"
# Import the Universal Sentence Encoder's TF Hub module
embed = hub.Module(module_url)

# Compute a representation for each message, showing various lengths supported.
messages = ["That band rocks!", "That song is really cool."]

with tf.Session() as session:
  session.run([tf.global_variables_initializer(), tf.tables_initializer()])
  message_embeddings = session.run(embed(messages))