src/snn_fine_tune.py [38:71]:
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    init_suncet_loss,
    make_labels_matrix
)
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']
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src/suncet_train.py [39:73]:
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    init_suncet_loss,
    make_labels_matrix
)
from src.data_manager import (
    init_data,
    make_transforms
)
from src.sgd import SGD
from src.lars import LARS

import apex
from torch.nn.parallel import DistributedDataParallel

# --
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):

    # ----------------------------------------------------------------------- #
    #  PASSED IN PARAMS FROM CONFIG FILE
    # ----------------------------------------------------------------------- #
    # -- META
    model_name = args['meta']['model_name']
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