Bump keras from 3.13.2 to 3.14.1 in /install

[dependabot]

Bumps keras from 3.13.2 to 3.14.1.

Release notes

Sourced from keras's releases.

v3.14.1

Saving & Reloading

• Harden path and link resolution when extracting files from archives (#22839)
  • Fixed link resolution bug when validating links extracted from TAR archives.
  • Fixed path confusion bug when validating files extracted from ZIP and TAR archives (including .keras files).
  • Added path validation when extracting assets from Orbax checkpoints.
• Harden H5 validation code and apply it to legacy .h5 files (#22801)
  • Disallow external links and virtual datasets in H5 files.
  • Also apply all the validation to the legacy .h5 file extraction.
• Improve validation and error reporting in functional model deserialization (#22800)
  • Detect loops in the graph when deserializing a functional model.
  • Improve error reporting for missing nodes in the graph.

Other Fixes

• Fix data sharding logic in ModelParallel (#22179)
• Fix regression with metrics passed to compile (#22663)
  • Fixed a regression introduced in #22308 where y_pred (as a list) and y_true (as a dict with keys matching Functional model output names) were not ordered identically and could be paired incorrectly.
• Fix regression preventing compilation with the L1L2 regularizer (#22629)
• Fix test compatibility with JAX 0.10.0 (#22694)

Full Changelog: keras-team/keras@v3.14.0...v3.14.1

v3.14.0

Highlights

• Orbax Checkpoint Integration: Full support for Orbax checkpoints, including sharding, remote paths, and step recovery.
• Quantization Upgrades: Added support for Activation-aware Weight Quantization (AWQ) and Asymmetric INT4 Sub-Channel Quantization.
• Batch Renormalization in BatchNorm: Added batch renormalization feature to the BatchRenormalization layer.
• New Optimizer: Added ScheduleFreeAdamW optimizer.
• Gated Attention: Introduced optional Gated Attention support in MultiHeadAttention and GroupedQueryAttention layers.

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New Features and Operations

Multi-Backend Operations

• NaN-aware NumPy Operations: Added support for nanmin, nanmax, nanmean, nanmedian, nanvar, nanstd, nanprod, nanargmin, nanargmax, and nanquantile in keras.ops.numpy.
• New Math & Linear Algebra Operators: Added nextafter, ptp, view, sinc, fmod, i0, fliplr, flipud, rad2deg, geomspace, depth_to_space, space_to_depth, and fold.

Preprocessing and Layers

• CLAHE Layer: Added Contrast Limited Adaptive Histogram Equalization preprocessing layer.
• Adapt Support for Iterables: Preprocessing layers now support Python iterables in the adapt() method, which allows the direct use of Grain datasets.

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OpenVINO Backend Support

The OpenVINO backend received a massive update, implementing a wide array of NumPy and Neural Network operations to achieve feature parity with other backends:

• NumPy Operations: vander, trapezoid, corrcoef, correlate, flip, diagonal, cbrt, hypot, trace, kron, argpartition, logaddexp2, ldexp, select, round, vstack, hsplit, vsplit, tile, nansum, tensordot, exp2, trunc, gcd, unravel_index, inner, cumprod, searchsorted, hanning, diagflat, norm, histogram, lcm, allclose, real, imag, isreal, kaiser, shuffle, einsum, quantile, conj, randint, in_top_k, signbit, gamma, heaviside, var, std, inv, solve, cholesky_inverse, fft, fft2, ifft2, rfft, irfft, stft, istft, scatter, binomial, unfold, QR decomposition, view, and more.

... (truncated)

Commits

• b7f0905 Patch release 3.14.1 (#22846)
• 050671c Keras Automations : Refine auto fix to add unit tests (#22624)
• 05bbdae Keras Automations: Refine Auto fix (#22623)
• 9708582 Implement nanmedian function in keras.ops (#22585)
• e0baba4 Revert "Pass the shape when creating a tf.Variable. (#22460)" (#22609)
• b8ba027 Keras Automations: Auto fix improve (#22613)
• d1e5f1c Keras automation: fix label name (#22611)
• a44d76e auto fix updates (#22610)
• 838b7e3 Fix TPU test broken in master. (#22605)
• 6c5956d [Fix] MelSpectrogram skips fft_length >= sequence_length validation for symbo...
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