Adding metrics to Callback functions + Fixing model summary issue

Summary

This MR introduces the following changes

• Fixing small issue with the model summary of the DenseNet.
• Removing history object from training.
• Training metrics are now saved via the MyCallback functions in a separate file.
• Two dicts are now written to disk when training: The train_metrics_dict.json and the normal validation.json with the parameters used for validation in the name of the file. The train_metrics_dict.json contains the train metrics, like accuracy, loss, learning rate, while the validation.json contains the same values (except learning rate) but for the validation dataset.
• If no validation dataset is given, only the train_metrics_dict.json is produced.
• Updating the get_validation_file_name function to get_metrics_file_name. Outputs now the path to the train_metrics_dict.json and the path + name for the validation.json.
• Unit tests are adapted.

Relates to the following issues

• Closes #173 (closed)

Conformity

• Changelog entry
• Documentation
• Development guidelines
• Style guides