kgcnn v4.0.1

• Removed unused layers and added manual built in scripts and training functions, since with keras==3.0.5 the pytorch trainer tries to rebuild the model,
  even if the model is already built and does it eagerly without proper tensor input, which causes crashes for almost every model in kgcnn.
• Fix Error in ExtensiveMolecularLabelScaler.transform missing default value.
• Added further benchmark results for kgcnn version 4.
• Fix error in kgcnn.layers.geom.PositionEncodingBasisLayer
• Fix error in kgcnn.literature.GCN.make_model_weighted
• Fix error in kgcnn.literature.AttentiveFP.make_model
• Had to change serialization for activation functions since with keras>=3.0.2 custom strings are not allowed also
  causing clashes with built-in functions. We catch defaults to be at least as backward compatible as possible and changed to serialization dictionary. Adapted all hyperparameter.
• Renamed leaky_relu and swish in kgcnn.ops.activ to leaky_relu2 and swish2.
• Fix error in jax scatter min/max functions.
• Added kgcnn.__safe_scatter_max_min_to_zero__ for tensorflow and jax backend scattering with default to True.
• Added simple ragged support for loss and metrics.
• Added simple ragged support for train_force.py
• Implemented random equivariant initialize for PAiNN
• Implemented charge and dipole output for HDNNP2nd
• Implemented jax backend for force models.
• Fix GraphBatchNormalization .
• Fix error in kgcnn.io.loader for unused IDs and graph state input.
• Added experimental DisjointForceMeanAbsoluteError