src/paws_train.py [45:81]:
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)
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']
    output_dim = args['meta']['output_dim']
    load_model = args['meta']['load_checkpoint']
    r_file = args['meta']['read_checkpoint']
    copy_data = args['meta']['copy_data']
    use_fp16 = args['meta']['use_fp16']
    use_pred_head = args['meta']['use_pred_head']
    device = torch.device(args['meta']['device'])
    torch.cuda.set_device(device)
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src/suncet_train.py [45:81]:
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)
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']
    output_dim = args['meta']['output_dim']
    load_model = args['meta']['load_checkpoint']
    r_file = args['meta']['read_checkpoint']
    copy_data = args['meta']['copy_data']
    use_fp16 = args['meta']['use_fp16']
    use_pred_head = args['meta']['use_pred_head']
    device = torch.device(args['meta']['device'])
    torch.cuda.set_device(device)
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