Develop Reference

No matching distribution found for tensorflow==1.15.2 in Google Colab

import tensorflow
print(tensorflow.__version__)
2.9.2
pip uninstall tensorflow
pip install tensorflow==1.15.2
Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
ERROR: Could not find a version that satisfies the requirement tensorflow==1.15.2 (from versions: 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0rc0, 2.6.0rc1, 2.6.0rc2, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0rc0, 2.7.0rc1, 2.7.0, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.0rc0, 2.8.0rc1, 2.8.0, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0rc0, 2.9.0rc1, 2.9.0rc2, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0rc0, 2.10.0rc1, 2.10.0rc2, 2.10.0rc3, 2.10.0, 2.10.1, 2.11.0rc0, 2.11.0rc1, 2.11.0rc2, 2.11.0)
ERROR: No matching distribution found for tensorflow==1.15.2
I used to use these libraries below by using tensorflow 1.15.2 in Google Colab. I could use pip install tensorflow 1.15.2 back in the days. But I cannot pip install tensorflow 1.15.2 anymore. I want to use these libraries below, how can I use them in Google Colab?
import tensorflow as tf
from tensorflow.contrib import rnn
from tensorflow.contrib import legacy_seq2seq

Tensorflow - install version 2.3.0

I'm currently running Tensorflow version 2.5.0 but I need to lower my version to 2.3.0.
I tried to install Tensorflow version 2.3.0 but I get this error:
ERROR: Could not find a version that satisfies the requirement tensorflow==2.3.0 (from versions: 2.5.0rc0, 2.5.0rc1, 2.5.0rc2, 2.5.0rc3, 2.5.0, 2.6.0rc0, 2.6.0rc1)
ERROR: No matching distribution found for tensorflow==2.3.0
I know its possible to build the pip package from the source code, but I was wondring if there is a better soultion.

Tensorflow 2.3.0 requires (and provides wheels for) Python 3.5, 3.6, 3.7, 3.8 but not 3.9 (and no source code). Downgrade Python to 3.8 or use a higher version of TF. Support for Python 3.9 started at version 2.5.0.

How to install version of tensorflow that isn't available through pip

I am attempting to install a specific version of tensorflow as part of the requirements for some code I'm trying to use (https://github.com/serengil/deepface)
When I attempt to install it like I normally do in command prompt I get the following.
C:\Windows\system32>pip install tensorflow==1.9.0
ERROR: Could not find a version that satisfies the requirement tensorflow==1.9.0 (from versions: 1.13.0rc1, 1.13.0rc2, 1.13.1, 1.13.2, 1.14.0rc0, 1.14.0rc1, 1.14.0, 1.15.0rc0, 1.15.0rc1, 1.15.0rc2, 1.15.0rc3, 1.15.0, 1.15.2, 1.15.3, 1.15.4, 2.0.0a0, 2.0.0b0, 2.0.0b1, 2.0.0rc0, 2.0.0rc1, 2.0.0rc2, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.1.0rc0, 2.1.0rc1, 2.1.0rc2, 2.1.0, 2.1.1, 2.1.2, 2.2.0rc0, 2.2.0rc1, 2.2.0rc2, 2.2.0rc3, 2.2.0rc4, 2.2.0, 2.2.1, 2.3.0rc0, 2.3.0rc1, 2.3.0rc2, 2.3.0, 2.3.1)
ERROR: No matching distribution found for tensorflow==1.9.0
I have referenced a few other Stackoverflow questions (Installing Tensorflow 1.9 in Windows) and haven't been able to find a solution or how to go about getting the version needed.

tensorflow==1.9.0 is available on PyPI (link). Your issue is that you are probably using Python 3.7, which 1.9.0 doesn't support, only Python 2.7 and 3.3 to 3.6. Install 64bit Python 3.6 and use it instead of 3.7.

Google API Core Library and Python version requirements

I'm using pipenv on a project with Python 3.6.4 and when installing dependencies I receive this error:
Could not find a version that matches futures>=3.2.0
Tried: 0.2.python3, 0.1, 0.2, 1.0, 2.0, 2.1, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.1.5, 2.1.5, 2.1.6, 2.1.6, 2.2.0, 2.2.0, 3.0.0, 3.0.0, 3.0.1, 3.0.1, 3.0.2, 3.0.2, 3.0.3, 3.0.3, 3.0.4, 3.0.4, 3.0.5, 3.0.5, 3.1.0, 3.1.0, 3.1.1, 3.1.1
After running pipenv lock -v I can see that google-api-core is a secondary dependency and it requires the following:
google-api-core==0.1.4 requires futures>=3.2.0; python_version < "3.2", google-auth<2.0.0dev,>=0.4.0, googleapis-common-protos<2.0dev,>=1.5.3, protobuf>=3.0.0, pytz, requests<3.0.0dev,>=2.18.0, setuptools>=34.0.0, six>=1.10.0
Does this mean that google-api-core requires the outdated Python 3.2?

Installing TensorFlow with Pip Python on Windows

Last month they released tensor-flow comparability with windows. Looking at the docs I've installed python 3.6 and run
pip install tensorflow-gpu
but it doesn't find it and therefore doesn't install it.
could not find a version that satisfies the requirements tensorflow-gpu(from versions)
Am I missing something basic? How can I fix or circumvent this?

A stable release of Python 3.6 for Windows became available on 12/23/2016, and we have not yet built TensorFlow packages for that version. (We will look into doing this after the holidays.) For now, your best options are:
Downgrade to Python 3.5 (64-bit version), which the pre-built packages support.
Try building TensorFlow from source.

Here is what i did to get tensorflow working with windows.
Download python 3.5.0 (64 bit from Python Releases for Windows)
Install it and check python version by running below command in cmd:
python --version
Python 3.5.0
Then run below command to upgrade pip to latest
python -m pip install --upgrade pip
Now install tensorflow using pip
pip install tensorflow
That's it you have installed tensorflow on windows. Below image shows what happens when you type above commands
Example to verify tensorflow is working.
$ python
...
import tensorflow as tf
hello = tf.constant('Hello, TensorFlow!')
sess = tf.Session()
print(sess.run(hello))

I think you have to install Python 3.5 not 3.6. I'm having the same problem.

pip3 install tensorflow==tensorflow_version
Available tensorflow versions: (0.12.1, 1.0.0, 1.0.1, 1.1.0rc0, 1.1.0rc1, 1.1.0rc2, 1.1.0, 1.2.0rc0, 1.2.0rc1, 1.2.0rc2, 1.2.0, 1.2.1, 1.3.0rc0, 1.3.0rc1, 1.3.0rc2, 1.3.0, 1.4.0rc0, 1.4.0rc1, 1.4.0, 1.4.1, 1.5.0rc0, 1.5.0rc1, 1.5.0, 1.5.1, 1.6.0rc0, 1.6.0rc1, 1.6.0, 1.7.0rc0, 1.7.0rc1, 1.7.0, 1.7.1, 1.8.0rc0, 1.8.0rc1, 1.8.0, 1.9.0rc0, 1.9.0rc1, 1.9.0rc2, 1.9.0, 1.10.0rc0, 1.10.0rc1, 1.10.0, 1.10.1, 1.11.0rc0, 1.11.0rc1, 1.11.0rc2, 1.11.0, 1.12.0rc0, 1.12.0rc1, 1.12.0rc2, 1.12.0, 1.12.2, 1.12.3, 1.13.0rc0, 1.13.0rc1, 1.13.0rc2, 1.13.1, 1.13.2, 1.14.0rc0, 1.14.0rc1, 1.14.0, 2.0.0a0, 2.0.0b0, 2.0.0b1)