Have you ever wondered how to know which TensorFlow version you have? Read this blog post to find out how to determine your TensorFlow version.
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This guide provides instructions on how to determine the TensorFlow version installed on your system.
What is TensorFlow?
TensorFlow is a powerful, open-source software library for data analysis and machine learning. Its core functionality is to define and optimize dataflow graphs—structure your machine learning algorithms in terms of computational operations, then arrange those operations into efficient networks. TensorFlow was developed by the Google Brain team for internal use at Google, and it was released under the Apache 2.0 open source license in November 2015.
TensorFlow has two types of releases:
1.1.0-rcX releases are available on GitHub. These are preview releases, and you should expect bugs and performance issues. We do not recommend using these releases for production purposes.
Stable releases provide security and bug fixes, but no new features.
How to Check Your TensorFlow Version
There are a few ways to check your TensorFlow version. The first is to simply print out the version string:
>>> import tensorflow as tf
If you installed TensorFlow using pip, you can also run the following command to get the version:
$ pip show tensorflow
Keeping Your TensorFlow Version Up-To-Date
TensorFlow is an open source machine learning platform used by developers and researchers to create sophisticated, scalable models to improve various aspects of their business or analyze data. The platform offers a wide variety of features and capabilities, which can be adapted to different use cases. However, as TensorFlow is constantly being updated with new features and improvements, it is important to keep your version up-to-date in order to take advantage of the latest improvements.
There are two ways to update your TensorFlow version: using a package manager or downloading the latest release from GitHub.
If you are using a package manager (e.g., pip), you can update TensorFlow by running the following command:
pip install – upgrade tensorflow
Alternatively, you can download the latest release from GitHub and install it manually. To do so, go to https://github.com/tensorflow/tensorflow/releases and download the file named tensorflow-VERSION-cpXX-cpXXm-win_amd64.whl (replace VERSION with the latest version number and cpXX with your Python version). Then, run the following command:
pip install tensorflow-VERSION-cpXX-cpXXm-win_amd64.whl
Finally, to know which version of TensorFlow you are using, you can simply type “python -c ‘import tensorflow as tf; print(tf.version)’” in your terminal.
Before starting, it is a good idea to have a basic understanding of the following concepts:
-TensorFlow is an open source software library for numerical computation using data flow graphs.
-Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them.
-TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google’s Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.
TensorFlow uses a major.minor.patch versioning scheme, where:
-Major release versions represent breaking changes to the TensorFlow API. Upgrading to a new major version usually requires changes to user code. We strive to minimize breaking changes in each major release, but sometimes they are necessary in order to add new features or fix critical bugs.
-Minor release versions are mostly compatible with prior minor versions within the same major version. New minor releases may add features that are backwards compatible with prior versions, and may also include bug fixes and other improvements. Minor releases should not introduce any breaking changes to the TensorFlow API.
-Patch releases are fully backwards compatible with prior versions and only include bug fixes and other improvements.
Keyword: How to Know the TensorFlow Version