'Load.
Restore model weights.
Arguments:
model_file: `str`. Model path.
optargs: optional extra arguments for trainer.restore (see helpers/trainer.py)
These optional arguments may be used to limit the scope of
variables restored, and to control whether a new session is
created for the restored variables.'

def load(self, model_file, **optargs):

    self.trainer.restore(model_file, **optargs)
    self.session = self.trainer.session
    self.predictor = Evaluator([self.net], session=self.session, model=None)
    for d in tf.get_collection(tf.GraphKeys.DATA_PREP):
        if d:
            d.restore_params(self.session)
