src/fine_tune.py [35:62]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
)
from src.data_manager import (
    init_data,
    make_transforms
)
from src.sgd import SGD
from torch.nn.parallel import DistributedDataParallel
from src.lars import LARS

# --
log_timings = True
log_freq = 10
checkpoint_freq = 50
# --

_GLOBAL_SEED = 0
np.random.seed(_GLOBAL_SEED)
torch.manual_seed(_GLOBAL_SEED)
torch.backends.cudnn.benchmark = True

logging.basicConfig(stream=sys.stdout, level=logging.INFO)
logger = logging.getLogger()


def main(args):

    # -- META
    model_name = args['meta']['model_name']
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



src/snn_fine_tune.py [40:71]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
)
from src.data_manager import (
    init_data,
    make_transforms
)

from src.sgd import SGD
from src.lars import LARS

from torch.nn.parallel import DistributedDataParallel

from snn_eval import main as val_run

# --
log_timings = True
log_freq = 10
checkpoint_freq = 50
# --

_GLOBAL_SEED = 0
np.random.seed(_GLOBAL_SEED)
torch.manual_seed(_GLOBAL_SEED)
torch.backends.cudnn.benchmark = True

logging.basicConfig(stream=sys.stdout, level=logging.INFO)
logger = logging.getLogger()


def main(args):

    # -- META
    model_name = args['meta']['model_name']
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -