dependabot[bot] opened a new pull request, #32026: URL: https://github.com/apache/beam/pull/32026
Bumps [tensorflow](https://github.com/tensorflow/tensorflow) from 2.11.1 to 2.12.1. <details> <summary>Release notes</summary> <p><em>Sourced from <a href="https://github.com/tensorflow/tensorflow/releases";>tensorflow's releases</a>.</em></p> <blockquote> <h2>TensorFlow 2.12.1</h2> <h1>Release 2.12.1</h1> <h3>Bug Fixes and Other Changes</h3> <ul> <li>The use of the ambe config to build and test aarch64 is not needed. The ambe config will be removed in the future. Making cpu_arm64_pip.sh and cpu_arm64_nonpip.sh more similar for easier future maintenance.</li> </ul> <h2>TensorFlow 2.12.0</h2> <h1>Release 2.12.0</h1> <h2>TensorFlow</h2> <h3>Breaking Changes</h3> <ul> <li> <p>Build, Compilation and Packaging</p> <ul> <li>Removed redundant packages <code>tensorflow-gpu</code> and <code>tf-nightly-gpu</code>. These packages were removed and replaced with packages that direct users to switch to <code>tensorflow</code> or <code>tf-nightly</code> respectively. Since TensorFlow 2.1, the only difference between these two sets of packages was their names, so there is no loss of functionality or GPU support. See <a href="https://pypi.org/project/tensorflow-gpu";>https://pypi.org/project/tensorflow-gpu</a> for more details.</li> </ul> </li> <li> <p><code>tf.function</code>:</p> <ul> <li><code>tf.function</code> now uses the Python inspect library directly for parsing the signature of the Python function it is decorated on. This change may break code where the function signature is malformed, but was ignored previously, such as: <ul> <li>Using <code>functools.wraps</code> on a function with different signature</li> <li>Using <code>functools.partial</code> with an invalid <code>tf.function</code> input</li> </ul> </li> <li><code>tf.function</code> now enforces input parameter names to be valid Python identifiers. Incompatible names are automatically sanitized similarly to existing SavedModel signature behavior.</li> <li>Parameterless <code>tf.function</code>s are assumed to have an empty <code>input_signature</code> instead of an undefined one even if the <code>input_signature</code> is unspecified.</li> <li><code>tf.types.experimental.TraceType</code> now requires an additional <code>placeholder_value</code> method to be defined.</li> <li><code>tf.function</code> now traces with placeholder values generated by TraceType instead of the value itself.</li> </ul> </li> <li> <p>Experimental APIs <code>tf.config.experimental.enable_mlir_graph_optimization</code> and <code>tf.config.experimental.disable_mlir_graph_optimization</code> were removed.</p> </li> </ul> <h3>Major Features and Improvements</h3> <ul> <li> <p>Support for Python 3.11 has been added.</p> </li> <li> <p>Support for Python 3.7 has been removed. We are not releasing any more patches for Python 3.7.</p> </li> <li> <p><code>tf.lite</code>:</p> <ul> <li>Add 16-bit float type support for built-in op <code>fill</code>.</li> <li>Transpose now supports 6D tensors.</li> <li>Float LSTM now supports diagonal recurrent tensors: <a href="https://arxiv.org/abs/1903.08023";>https://arxiv.org/abs/1903.08023</a></li> </ul> </li> <li> <p><code>tf.experimental.dtensor</code>:</p> <ul> <li>Coordination service now works with <code>dtensor.initialize_accelerator_system</code>, and enabled by default.</li> <li>Add <code>tf.experimental.dtensor.is_dtensor</code> to check if a tensor is a DTensor instance.</li> </ul> </li> <li> <p><code>tf.data</code>:</p> <ul> <li>Added support for alternative checkpointing protocol which makes it possible to checkpoint the state of the input pipeline without having to store the contents of internal buffers. The new functionality can be enabled through the <code>experimental_symbolic_checkpoint</code> option of <code>tf.data.Options()</code>.</li> <li>Added a new <code>rerandomize_each_iteration</code> argument for the <code>tf.data.Dataset.random()</code> operation, which controls whether the sequence of generated random numbers should be re-randomized every epoch or not (the default behavior). If <code>seed</code> is set and <code>rerandomize_each_iteration=True</code>, the <code>random()</code> operation will produce a different (deterministic) sequence of numbers every epoch.</li> </ul> </li> </ul> <!-- raw HTML omitted --> </blockquote> <p>... (truncated)</p> </details> <details> <summary>Changelog</summary> <p><em>Sourced from <a href="https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md";>tensorflow's changelog</a>.</em></p> <blockquote> <h1>Release 2.12.1</h1> <h3>Bug Fixes and Other Changes</h3> <ul> <li>The use of the ambe config to build and test aarch64 is not needed. The ambe config will be removed in the future. Making cpu_arm64_pip.sh and cpu_arm64_nonpip.sh more similar for easier future maintenance.</li> </ul> <h1>Release 2.12.0</h1> <h3>Breaking Changes</h3> <ul> <li> <p>Build, Compilation and Packaging</p> <ul> <li>Removed redundant packages <code>tensorflow-gpu</code> and <code>tf-nightly-gpu</code>. These packages were removed and replaced with packages that direct users to switch to <code>tensorflow</code> or <code>tf-nightly</code> respectively. Since TensorFlow 2.1, the only difference between these two sets of packages was their names, so there is no loss of functionality or GPU support. See <a href="https://pypi.org/project/tensorflow-gpu";>https://pypi.org/project/tensorflow-gpu</a> for more details.</li> </ul> </li> <li> <p><code>tf.function</code>:</p> <ul> <li><code>tf.function</code> now uses the Python inspect library directly for parsing the signature of the Python function it is decorated on. This change may break code where the function signature is malformed, but was ignored previously, such as: <ul> <li>Using <code>functools.wraps</code> on a function with different signature</li> <li>Using <code>functools.partial</code> with an invalid <code>tf.function</code> input</li> </ul> </li> <li><code>tf.function</code> now enforces input parameter names to be valid Python identifiers. Incompatible names are automatically sanitized similarly to existing SavedModel signature behavior.</li> <li>Parameterless <code>tf.function</code>s are assumed to have an empty <code>input_signature</code> instead of an undefined one even if the <code>input_signature</code> is unspecified.</li> <li><code>tf.types.experimental.TraceType</code> now requires an additional <code>placeholder_value</code> method to be defined.</li> <li><code>tf.function</code> now traces with placeholder values generated by TraceType instead of the value itself.</li> </ul> </li> <li> <p>Experimental APIs <code>tf.config.experimental.enable_mlir_graph_optimization</code> and <code>tf.config.experimental.disable_mlir_graph_optimization</code> were removed.</p> </li> </ul> <h3>Major Features and Improvements</h3> <ul> <li> <p>Support for Python 3.11 has been added.</p> </li> <li> <p>Support for Python 3.7 has been removed. We are not releasing any more patches for Python 3.7.</p> </li> <li> <p><code>tf.lite</code>:</p> <ul> <li>Add 16-bit float type support for built-in op <code>fill</code>.</li> <li>Transpose now supports 6D tensors.</li> <li>Float LSTM now supports diagonal recurrent tensors: <a href="https://arxiv.org/abs/1903.08023";>https://arxiv.org/abs/1903.08023</a></li> </ul> </li> <li> <p><code>tf.experimental.dtensor</code>:</p> <ul> <li>Coordination service now works with <code>dtensor.initialize_accelerator_system</code>, and enabled by default.</li> <li>Add <code>tf.experimental.dtensor.is_dtensor</code> to check if a tensor is a DTensor instance.</li> </ul> </li> <li> <p><code>tf.data</code>:</p> <ul> <li>Added support for alternative checkpointing protocol which makes it possible to checkpoint the state of the input pipeline without having to store the contents of internal buffers. The new functionality can be enabled through the <code>experimental_symbolic_checkpoint</code> option of <code>tf.data.Options()</code>.</li> <li>Added a new <code>rerandomize_each_iteration</code> argument for the <code>tf.data.Dataset.random()</code> operation, which controls whether the sequence of generated random numbers should be re-randomized every epoch or not (the default behavior). If <code>seed</code> is set and <code>rerandomize_each_iteration=True</code>, the <code>random()</code> operation will produce a different (deterministic) sequence of numbers every epoch.</li> <li>Added a new <code>rerandomize_each_iteration</code> argument for the <code>tf.data.Dataset.sample_from_datasets()</code> operation, which controls whether the sequence of generated random numbers used for sampling should be re-randomized every epoch or not. If <code>seed</code> is set and <code>rerandomize_each_iteration=True</code>, the <code>sample_from_datasets()</code> operation will use a different (deterministic) sequence of numbers every epoch.</li> </ul> </li> <li> <p><code>tf.test</code>:</p> </li> </ul> <!-- raw HTML omitted --> </blockquote> <p>... (truncated)</p> </details> <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/tensorflow/tensorflow/commit/8e2b6655c0c488290179ab90a0daed0f6d3006f7";><code>8e2b665</code></a> Merge pull request <a href="https://redirect.github.com/tensorflow/tensorflow/issues/61094";>#61094</a> from tensorflow/venkat-patch-444</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/02478f09201719a94c7eb01a0e280b65d8fff261";><code>02478f0</code></a> Fix unit test failure caused by numpy update</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/2cd9b4143cb19335fdbd06aa6ecc3ecdae474fb8";><code>2cd9b41</code></a> Merge pull request <a href="https://redirect.github.com/tensorflow/tensorflow/issues/61082";>#61082</a> from tensorflow/venkat-patch-333</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/7995c95fb197f11dcf4635a719668e10f9700c38";><code>7995c95</code></a> Updating Simplified retry logic to DNS cache</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/29479edb66c12159ef6a1ecf6af6fbd665a1c9f6";><code>29479ed</code></a> Merge pull request <a href="https://redirect.github.com/tensorflow/tensorflow/issues/60872";>#60872</a> from tensorflow/r2.12-c45a6c0b1cb</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/e76a9332a2801fdabc4c5692b389c708fa79d8e0";><code>e76a933</code></a> Simplified retry logic to DNS cache</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/76addf724a4794222e780542180dc32747d04aa2";><code>76addf7</code></a> Merge pull request <a href="https://redirect.github.com/tensorflow/tensorflow/issues/60850";>#60850</a> from elfringham/non_pip_fix</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/05987a86af6544e8a93182c7f898465a87066a57";><code>05987a8</code></a> [Linaro:ARM_CI] Fix permissions for running nonpip tests</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/23724d2f60835df36f0cfe8b78f9d2c6e8085663";><code>23724d2</code></a> Merge pull request <a href="https://redirect.github.com/tensorflow/tensorflow/issues/60842";>#60842</a> from elfringham/r2.12</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/496730b8b5007e1cea0b609a3de45e5082dcd685";><code>496730b</code></a> Limit typing_extensions to less than 4.6.0 until it works</li> <li>Additional commits viewable in <a href="https://github.com/tensorflow/tensorflow/compare/v2.11.1...v2.12.1";>compare view</a></li> </ul> </details> <br /> [](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores) Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting `@dependabot rebase`. [//]: # (dependabot-automerge-start) [//]: # (dependabot-automerge-end) --- <details> <summary>Dependabot commands and options</summary> <br /> You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot show <dependency name> ignore conditions` will show all of the ignore conditions of the specified dependency - `@dependabot ignore this major version` will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this minor version` will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this dependency` will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself) You can disable automated security fix PRs for this repo from the [Security Alerts page](https://github.com/apache/beam/network/alerts). </details> -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
