LAP/torchlap/experiments/_model_loading.py

from os import path
from typing import TYPE_CHECKING
import torch
from ..models.model import Model
if TYPE_CHECKING:
    from ..configs.base_config import BaseConfig


def load_model(the_model: Model, conf: 'BaseConfig') -> Model:

    dev_name = conf.dev_name

    if conf.final_model_dir is not None:
        load_dir = conf.final_model_dir
        if not path.exists(load_dir):
            raise Exception('No path %s' % load_dir)
    else:
        load_dir = conf.save_dir

    print('>>> loading from: ' + load_dir, flush=True)
    if not path.exists(load_dir):
        raise Exception('Problem in loading the model. %s does not exist!' % load_dir)

    map_location = None
    if dev_name == 'cpu':
        map_location = 'cpu'
    elif dev_name is not None and ':' in dev_name:
        map_location = dev_name

    the_model.to(conf.device)

    if path.isfile(load_dir):

        if not path.exists(load_dir):
            raise Exception('Problem in loading the model. %s does not exist!' % load_dir)

        the_model.load_state_dict(torch.load(load_dir, map_location=map_location))
        print('Loaded the model at %s' % load_dir, flush=True)

    else:
        if conf.epoch is not None:
            epoch = int(conf.epoch)
        elif path.exists(load_dir + '/GeneralInfo'):
            checkpoint = torch.load(load_dir + '/GeneralInfo', map_location=map_location)
            epoch = checkpoint['best_val_epoch']
            print(f'Epoch has not been specified in the config, '
                    f'using {epoch} which is best_val_epoch instead')
        else:
            raise Exception('Either epoch or pt dir (final_model) must be given as GeneralInfo was not found')

        if not path.exists('%s/%d' % (load_dir, epoch)):
            raise Exception('Problem in loading the model. %s/%d does not exist!' %
                            (load_dir, epoch))

        checkpoint = torch.load('%s/%d' % (load_dir, epoch),
                                map_location=map_location)

        # backward compatibility
        if 'model_state_dict' in checkpoint:
            checkpoint = checkpoint['model_state_dict']

        the_model.load_state_dict(checkpoint)

        print(f'Loaded the model from epoch {epoch} of {load_dir}', flush=True)

    the_model.to(conf.device)

    return the_model