pyanomaly/core/engine/abstract/base_engine.py
def resume(self):
        """Load files used for resume training.
        The method loads the model file and the optimzier file.
        """
        logger.info('=> Resume the previous training')
        checkpoint_path = self.config.TRAIN.resume.checkpoint_path
        logger.info(f'=> Load the checkpoint from {checkpoint_path}')
        checkpoint = torch.load(checkpoint_path)
        # self.model.load_state_dict(checkpoint['model_state_dict'])
        self._load_file(self.model.keys(), checkpoint['model_state_dict'])
        # self.optimizer.load_state_dict(checkpoint['optimizer_state_dict'])
        self._load_file(self.optimizer.keys(), checkpoint['optimizer_state_dict'])
Load files used for resume training.
        The method loads the model file and the optimzier file.
        
Load files used for resume training.
The method loads the model file and the optimzier file.
Load files used for resume training . The method loads the model file and the optimzier file .
def resume(self):
        logger.info('=> Resume the previous training')
        checkpoint_path = self.config.TRAIN.resume.checkpoint_path
        logger.info(f'=> Load the checkpoint from {checkpoint_path}')
        checkpoint = torch.load(checkpoint_path)
        self._load_file(self.model.keys(), checkpoint['model_state_dict'])
        self._load_file(self.optimizer.keys(), checkpoint['optimizer_state_dict'])
def resume ( self ) : logger . info ( '=> Resume the previous training' ) checkpoint_path = self . config . TRAIN . resume . checkpoint_path logger . info ( f'=> Load the checkpoint from {checkpoint_path}' ) checkpoint = torch . load ( checkpoint_path ) self . _load_file ( self . model . keys ( ) , checkpoint [ 'model_state_dict' ] ) self . _load_file ( self . optimizer . keys ( ) , checkpoint [ 'optimizer_state_dict' ] )
Load files used for resume training.
Load files used for resume training .
"""Load files used for resume training.
        The method loads the model file and the optimzier file.
        """ # self.model.load_state_dict(checkpoint['model_state_dict'])
 # self.optimizer.load_state_dict(checkpoint['optimizer_state_dict'])

self