Colab Kernel Restarts Whenever Loading a Model From Tensorflow-hub - tensorflow

Question

I wanted to try out the embeddings provided in tensorflow-hub, the 'universal-sentence-encoder' to be specific. I tried the examples provided (https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/semantic_similarity_with_tf_hub_universal_encoder.ipynb)
and it worked fine. So I tried to do the same with 'multilingual' model but every time the multilingual model is loaded, the colab kernel fails and restarts. What is the problem and how can I get around this?
import tensorflow as tf
import tensorflow_hub as hub
import matplotlib.pyplot as plt
import numpy as np
import os
import pandas as pd
import re
import seaborn as sns
import tf_sentencepiece
import sentencepiece
# Import the Universal Sentence Encoder's TF Hub module
embed = hub.Module("https://tfhub.dev/google/universal-sentence-encoder-multilingual/1") // This is where the kernel dies.
print("imported model")
# Compute a representation for each message, showing various lengths supported.
word = "코끼리"
sentence = "나는 한국어로 쓰여진 문장이야."
paragraph = (
"동해물과 백두산이 마르고 닳도록. "
"하느님이 보우하사 우리나라 만세~")
messages = [word, sentence, paragraph]
# Reduce logging output.
tf.logging.set_verbosity(tf.logging.ERROR)
with tf.Session() as session:
session.run([tf.global_variables_initializer(), tf.tables_initializer()])
message_embeddings = session.run(embed(messages))
for i, message_embedding in enumerate(np.array(message_embeddings).tolist()):
print("Message: {}".format(messages[i]))
print("Embedding size: {}".format(len(message_embedding)))
message_embedding_snippet = ", ".join(
(str(x) for x in message_embedding[:3]))
print("Embedding: [{}, ...]\n".format(message_embedding_snippet))

Answer 1

I had similar issues with the multilingual sentence encoder. I resolved it by specifying tensorflow version to 1.14.0 and tf-sentencepiece to 0.1.83, so before running your code in colab try:
!pip3 install tensorflow==1.14.0
!pip3 install tensorflow-hub
!pip3 install sentencepiece
!pip3 install tf-sentencepiece==0.1.83
I was able to replicate your problem in colab and this solution loaded the model correctly:
It seems to be a compatibility problem between sentencepiece and tensorflow, check for updates on this issue here.
Let us know how it goes. Best of luck and I hope this helps.
EDIT: If tensorflow version 1.14.0 does not work, change it to 1.13.1. This problem should be resolved once compatibility between tensorflow and sentencepiece is figured it out.