hub: Some hub symbols are not available because TensorFlow version is less than 1.14

In Debian, Python3, using pip3 install I got: sudo pip3 install --upgrade tensorflow

Requirement already up-to-date: tensorflow in /usr/local/lib/python3.7/dist-packages (1.13.1)
Requirement already satisfied, skipping upgrade: wheel>=0.26 in /usr/local/lib/python3.7/dist-packages (from tensorflow) (0.33.1)
Requirement already satisfied, skipping upgrade: six>=1.10.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow) (1.10.0)
Requirement already satisfied, skipping upgrade: tensorboard<1.14.0,>=1.13.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow) (1.13.1)
Requirement already satisfied, skipping upgrade: absl-py>=0.1.6 in /usr/local/lib/python3.7/dist-packages (from tensorflow) (0.7.1)
Requirement already satisfied, skipping upgrade: protobuf>=3.6.1 in /usr/local/lib/python3.7/dist-packages (from tensorflow) (3.7.1)
Requirement already satisfied, skipping upgrade: gast>=0.2.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow) (0.2.2)
Requirement already satisfied, skipping upgrade: astor>=0.6.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow) (0.7.1)
Requirement already satisfied, skipping upgrade: numpy>=1.13.3 in /usr/local/lib/python3.7/dist-packages (from tensorflow) (1.16.2)
Requirement already satisfied, skipping upgrade: termcolor>=1.1.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow) (1.1.0)
Requirement already satisfied, skipping upgrade: tensorflow-estimator<1.14.0rc0,>=1.13.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow) (1.13.0)
Requirement already satisfied, skipping upgrade: keras-applications>=1.0.6 in /usr/local/lib/python3.7/dist-packages (from tensorflow) (1.0.7)
Requirement already satisfied, skipping upgrade: grpcio>=1.8.6 in /usr/local/lib/python3.7/dist-packages (from tensorflow) (1.19.0)
Requirement already satisfied, skipping upgrade: keras-preprocessing>=1.0.5 in /usr/local/lib/python3.7/dist-packages (from tensorflow) (1.0.9)
Requirement already satisfied, skipping upgrade: werkzeug>=0.11.15 in /usr/local/lib/python3.7/dist-packages (from tensorboard<1.14.0,>=1.13.0->tensorflow) (0.15.2)
Requirement already satisfied, skipping upgrade: markdown>=2.6.8 in /usr/local/lib/python3.7/dist-packages (from tensorboard<1.14.0,>=1.13.0->tensorflow) (3.1)
Requirement already satisfied, skipping upgrade: setuptools in /usr/lib/python3/dist-packages (from protobuf>=3.6.1->tensorflow) (40.8.0)
Requirement already satisfied, skipping upgrade: mock>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow-estimator<1.14.0rc0,>=1.13.0->tensorflow) (2.0.0)
Requirement already satisfied, skipping upgrade: h5py in /usr/local/lib/python3.7/dist-packages (from keras-applications>=1.0.6->tensorflow) (2.9.0)
Requirement already satisfied, skipping upgrade: pbr>=0.11 in /usr/local/lib/python3.7/dist-packages (from mock>=2.0.0->tensorflow-estimator<1.14.0rc0,>=1.13.0->tensorflow) (5.1.3)

Now, using code from medium.com, I got warnings:

W0409 15:51:29.103832 140123364300608 __init__.py:56] Some hub symbols are not available because TensorFlow version is less than 1.14
W0409 15:51:29.888326 140123364300608 deprecation.py:323] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/ops/control_flow_ops.py:3632: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:

Why is that happening and how can one avoid it? How could I install newer version with pip, not from git? Thanks!

About this issue

Original URL
State: closed
Created 5 years ago
Comments: 18 (3 by maintainers)

Commits related to this issue

Tone down log message to avoid misunderstandings as in https://github.com/tensorflow/hub/issues/276 PiperOrigin-RevId: 243994689 — committed to tensorflow/hub by a-googler 5 years ago

Most upvoted comments

Hi, Did you install “tf-nightly”? That helped me. BR

AnnettAnd on May 20, 2019

It is a #$%&/() mess. v2 is completely incompatible with v1.

tvrbanec on Apr 10, 2019

Thanks, but migration guide isn’t helpful. For example, how would you translate:

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

Migration guide:

Replace tf.Session.run calls
Every tf.Session.run call should be replaced by a Python function.
The feed_dict and tf.placeholders become function arguments.
The fetches become the function's return value.

tvrbanec on Apr 12, 2019