v24.12.0 release

Release notes as follows:

• Enables saving models to cloud storage and precomputed k-NN argument in UMAP.
• Uses improved precision GPU kernels for mean and variance in logistic regression.
• Updates RAPIDS dependencies to 24.12.
• Updates Dataproc notebook and benchmark examples.
• Multiple bug fixes for multi-gpu nodes, ivf_pq with cagra build, logistic regression training and estimator copy.

pip package available at https://pypi.org/project/spark-rapids-ml/24.12.0/

Known issues:

• Enabling UVM for DBSCAN and KNN may cause seg-faults on some multi-gpu instances.
• NCCL hangs in some algos on some multi-gpu instances.
• Supplying both param sample fraction and precomputed kNN to UMAP can trigger obscure cuda error.
• Model copy with parameter value update results in an error.