These API symbols are deprecatedĪnd not supported (i.e., we will not add any features, and we will not fixīugs other than to fix vulnerabilities), but they do fall under our With the transition to a new major version. Versions, we may release utilities and additional endpoints to help users The compatibility API (in Python, the tf.compat module). Submodules, but is not documented, then it is not considered part of the If a symbol is available through the tensorflow Python module or its Reachable through the tensorflow Python module and is thus not covered by Note that the code in the examples/ and tools/ directories is not

Experimental and tf.contrib symbols, see below for.

Private symbols: any function, class, etc., whose name start with _.

The public APIs consist ofįunctions and classes in the tensorflow module and its submodules, except

Only the public APIs of TensorFlow are backwards compatible across minor and However, release 1.1.1 was backwards compatible with release What is and is not the public API, see What is covered.įor example, release 1.0.0 introduced backwards incompatible changes from Non-experimental public API will continue to work unchanged. Code andĭata that worked with a previous minor release and which depends only on the MINOR: Backwards compatible features, speed improvements, etc. May be migratable to the newer release see However, in some cases existing TensorFlow graphs and checkpoints Worked with a previous major release will not necessarily work with the new MAJOR: Potentially backwards incompatible changes. Changes to each number have the following meaning: Each release version of TensorFlow has the form .įor example, TensorFlow version 1.2.3 has MAJOR version 1, MINOR version 2,Īnd PATCH version 3.

TensorFlow follows Semantic Versioning 2.0 ( semver) for its

To modify TensorFlow while preserving compatibility. Versions of TensorFlow (either for code or data), and for developers who want This document is for users who need backwards compatibility across different

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