dependabot[bot] opened a new pull request, #36666: URL: https://github.com/apache/beam/pull/36666
Bumps [keras](https://github.com/keras-team/keras) from 3.10.0 to 3.12.0. <details> <summary>Release notes</summary> <p><em>Sourced from <a href="https://github.com/keras-team/keras/releases";>keras's releases</a>.</em></p> <blockquote> <h2>Keras 3.12.0</h2> <h2>Highlights</h2> <h3>Keras has a new model distillation API!</h3> <p>You now have access to an easy-to-use API for distilling large models into small models while minimizing performance drop on a reference dataset -- compatible with all existing Keras models. You can specify a range of different distillation losses, or create your own losses. The API supports multiple concurrent distillation losses at the same time.</p> <p>Example:</p> <pre lang="python"><code># Load a model to distill teacher = ... # This is the model we want to distill it into student = ... <h1>Configure the process</h1> <p>distiller = Distiller( teacher=teacher, student=student, distillation_losses=LogitsDistillation(temperature=3.0), ) distiller.compile( optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'] )</p> <h1>Train the distilled model</h1> <p>distiller.fit(x_train, y_train, epochs=10) </code></pre></p> <h3>Keras supports GPTQ quantization!</h3> <p>GPTQ is now built into the Keras API. GPTQ is a post-training, weights-only quantization method that compresses a model to int4 layer by layer. For each layer, it uses a second-order method to update weights while minimizing the error on a calibration dataset.</p> <p>Learn how to use it <a href="https://keras.io/guides/gptq_quantization_in_keras/";>in this guide</a>.</p> <p>Example:</p> <pre lang="python"><code>model = keras_hub.models.Gemma3CausalLM.from_preset("gemma3_1b") gptq_config = keras.quantizers.GPTQConfig( dataset=calibration_dataset, tokenizer=model.preprocessor.tokenizer, weight_bits=4, group_size=128, num_samples=256, sequence_length=256, hessian_damping=0.01, symmetric=False, </tr></table> </code></pre> </blockquote> <p>... (truncated)</p> </details> <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/keras-team/keras/commit/adbfd13426a0da9864d9a0fcd5be5eed74ca341f";><code>adbfd13</code></a> Add warning to <code>set_backend</code> and more detailed example. (<a href="https://redirect.github.com/keras-team/keras/issues/21787";>#21787</a>)</li> <li><a href="https://github.com/keras-team/keras/commit/70598b7903314f7ceace49264de97f1ee91230a8";><code>70598b7</code></a> Fix typo in Distiller docstring</li> <li><a href="https://github.com/keras-team/keras/commit/eecd34f406709e6ce44c5d94be32d8d81c7fe13d";><code>eecd34f</code></a> Fix: <code>keras.ops.quantile</code> works with tf graph execution (<a href="https://redirect.github.com/keras-team/keras/issues/21782";>#21782</a>)</li> <li><a href="https://github.com/keras-team/keras/commit/c2bc6cfcc79d958d2e5a9bc0c829486d5a7fd0ac";><code>c2bc6cf</code></a> Suport keras.op.view() to view the same data bitwise at a new dtype (<a href="https://redirect.github.com/keras-team/keras/issues/21763";>#21763</a>)</li> <li><a href="https://github.com/keras-team/keras/commit/10b51ce5a5054eb9bcddfab405ac9075fb1f1ca7";><code>10b51ce</code></a> Make confusion metrics compilable. (<a href="https://redirect.github.com/keras-team/keras/issues/21775";>#21775</a>)</li> <li><a href="https://github.com/keras-team/keras/commit/18f79d69c9443b21ac4ac902a5f808237708cdde";><code>18f79d6</code></a> Fix negative index handling in MultiHeadAttention attention_axes (<a href="https://redirect.github.com/keras-team/keras/issues/21721";>#21721</a>)</li> <li><a href="https://github.com/keras-team/keras/commit/18e0364cbcd1bfe26e43a4986df59bbf758e94a8";><code>18e0364</code></a> Support for extracting volume patches (<a href="https://redirect.github.com/keras-team/keras/issues/21759";>#21759</a>)</li> <li><a href="https://github.com/keras-team/keras/commit/dc5e42cca4fc966916552154d2edfb9f9aef3fcf";><code>dc5e42c</code></a> fix sas metrics in jax <code>fit</code> (<a href="https://redirect.github.com/keras-team/keras/issues/21765";>#21765</a>)</li> <li><a href="https://github.com/keras-team/keras/commit/1ba3b8f896fbbba30bdcff65483b1dafa356c604";><code>1ba3b8f</code></a> Fix discretization discrepancy (<a href="https://redirect.github.com/keras-team/keras/issues/21769";>#21769</a>)</li> <li><a href="https://github.com/keras-team/keras/commit/53987a768def7fb4d6222d5da25484ea4ed76360";><code>53987a7</code></a> Document that <code>set_backend</code> requires re-importing keras. (<a href="https://redirect.github.com/keras-team/keras/issues/21764";>#21764</a>)</li> <li>Additional commits viewable in <a href="https://github.com/keras-team/keras/compare/v3.10.0...v3.12.0";>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`. 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