Adding conditional attention

This MR adds the following:

• Adding new train script for DIPS Conditional Attention + example train config.
• Adding support for new DIPS Conditional Attention model in the validation/evaluation chain.
• Adding integration test for train/validation/evaluation of DIPS Conditional Attention.
• Fixing some issues in the tf_tools/models with the masking (also adapted the unit test).
• Adding new generator for DIPS Conditional Attention.
• Adding some flexibility to the loading of the loading_validation_data functions.
• Adding compatibility of the evaluate_model.py for DIPS and DIPS Conditional Attention.
• Adding DIPS Conditional Attention to possible models for plotting_epoch_performance.py
• Adding DIPS Conditional Attention train script to the setup.py.
• Make the calculation of the Saliency maps steerable in the train config of the DIPS models.