Update keras requirement from <2.16,>=2.15 to >=2.15,<3.15 in /models

[dependabot]

Updates the requirements on keras to permit the latest version.

Release notes

Sourced from keras's releases.

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.
• Neural Network Operations: Added support for separable_conv, conv_transpose, adaptive_average_pool, adaptive_max_pool, RNN, LSTM, and GRU.
• Control Flow Operations: Implemented cond, scan, associative_scan, map, switch, fori_loop, and vectorized_map.

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Bug Fixes and Improvements

Backend Specific Improvements

• PyTorch: Dynamic shapes support in export, device selection improvements, and bug fixes to the CuDNN based LSTM and GRU implementation.
• JAX: Improved RNG handling in FlaxLayer and JaxLayer, variable jitting improvements, and direct JAX-to-ONNX export.
• NumPy: Enabled masking support for the NumPy backend.

Other Improvements

• Fixed multiple symbolic shape bugs across layers like Conv1DTranspose, IndexLookup, and TextVectorization.
• Fixed activity regularizer normalization by batch size.
• Improved Sequential error messages for incompatible layers.
• Minimized memory usage issues in sparse_categorical_crossentropy.

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New Contributors

We would like to thank our new contributors for making their first contribution to the Keras project:

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Commits

• 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...
• 99dda4c [OpenVINO] Fix float16 dtype promotion in OpenVINOKerasTensor binary operator...
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