![]() For example, TensorFlow 2.3.0, 2.3.1, and 2.3.2 are all minor releases. The Minor release versions are indicated by the second digit in the version number. Major releases typically introduce significant changes to the TensorFlow API and may require changes to your existing code. For example, TensorFlow 2.0, 2.1, and 2.2 are all Major releases. The Major release versions are indicated by the first digit in the version number. ![]() There are two types of releases: Major and Minor. TensorFlow is released regularly, and each release comes with its own set of features and bug fixes. Understanding the Different TensorFlow Release Versions Take note of the version number as you will need it later. Major releases that involve any changes to dependencies (like updating to pangolin v4.0) will need to also update the pangolin environment using the instructions below.This will display information about the TensorFlow package installed on your machine, including the version number. ![]() Note: The update flags will update versions of pangolin, pangolin-data, scorpio and constellations to the latest tagged releases. conda env update -f environment.yml updates the conda environment.git pull pulls the latest changes from github.Navigate to your local directory where you cloned the pangolin repository on the command line. If you used conda (or mamba) to install pangolin, conda activate the environment in which you installed pangolin if it's not already activated, and then update: For Major Releases: Updating a Bioconda or Mamba installation Back to pangolin documentation home page.
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