'Returns a map of variables to load from a foreign checkpoint.
Returns a map of variable names to load from a checkpoint to variables in
the model graph. This enables the model to initialize based on weights from
another task. For example, the feature extractor variables from a
classification model can be used to bootstrap training of an object
detector. When loading from an object detection model, the checkpoint model
should have the same parameters as this detection model with exception of
the num_classes parameter.
Args:
from_detection_checkpoint: whether to restore from a full detection
checkpoint (with compatible variable names) or to restore from a
classification checkpoint for initialization prior to training.
Returns:
A dict mapping variable names (to load from a checkpoint) to variables in
the model graph.'

@abstractmethod
def restore_map(self, from_detection_checkpoint=True):

    pass
