MultiModalPredictor.load#

classmethod MultiModalPredictor.load(path: str, resume: bool | None = False, verbosity: int | None = 3)[source]#

Load a predictor object from a directory specified by path. The to-be-loaded predictor can be completely or partially trained by .fit(). If a previous training has completed, it will load the checkpoint model.ckpt. Otherwise, if a previous training accidentally collapses in the middle, it can load the last.ckpt checkpoint by setting resume=True. It also supports loading one specific checkpoint given its path.

Parameters:

  • path – The directory to load the predictor object.

  • resume – Whether to resume training from last.ckpt. This is useful when a training was accidentally broken during the middle, and we want to resume the training from the last saved checkpoint.

  • verbosity – Verbosity levels range from 0 to 4 and control how much information is printed. Higher levels correspond to more detailed print statements. You can set verbosity = 0 to suppress warnings.

Return type:

The loaded predictor object.