google / sedpack / 31358162863
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Bump keras from 3.14.0 to 3.15.0 (#391)

Bumps [keras](https://github.com/keras-team/keras) from 3.14.0 to
3.15.0.
<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>v3.15.0</h2>
<h2>Highlights</h2>
<ul>
<li><strong>Keras-to-Torch Export</strong>: New
<code>export_torch</code> enables exporting Keras models to native
PyTorch <code>nn.Module</code> format, along with LiteRT (TFLite) export
support for the PyTorch backend.</li>
<li><strong>Sliding Window Attention</strong>: Added
<code>sliding_window</code> parameter to <code>MultiHeadAttention</code>
and <code>GroupedQueryAttention</code> for efficient long-context
attention.</li>
<li><strong>Flash / Fused SDPA</strong>: Causal-only MHA/GQA now
automatically dispatches to Flash Attention (cuDNN SDPA), and the manual
attention path correctly applies causal masking.</li>
<li><strong>Multi-Optimizer Training</strong>: New
<code>MultiOptimizer</code> supports assigning different optimizers to
sub-networks.</li>
<li><strong>New Math Operations</strong>: Added <code>unique</code>,
<code>pinv</code>, <code>matrix_rank</code>, <code>fabs</code>,
<code>fmax</code>, <code>fmin</code>, <code>erfc</code>,
<code>dsplit</code>, <code>percentile</code>,
<code>nanpercentile</code>, <code>sobel_edges</code>, and
<code>ssim</code> (structural similarity) to
<code>keras.ops</code>.</li>
<li><strong>Security Hardening</strong>: Comprehensive hardening of
model reloading against HDF5 exploits, tar/zip traversal attacks,
insecure deserialization.</li>
</ul>
<hr />
<h2>New Features and Operations</h2>
<h3>Multi-Backend Operations</h3>
<ul>
<li><strong>New NumPy Operations</strong>: Added <code>unique</code>,
<code>fabs</code>, <code>fmax</code>, <code>fmin</code>,
<code>dsplit</code>, <code>erfc</code>, <code>percentile</code>,
<code>nanpercentile</code> in <code>keras.ops.numpy</code>.</li>
<li><strong>New Line... (continued)

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