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from easydict import EasyDict as edict
# make training faster
# our RAM is 256G
# mount -t tmpfs -o size=140G tmpfs /train_tmp
config = edict()
config.loss = "arcface"
config.network = "r50"
config.resume = False
config.output = "ms1mv3_arcface_r50"
config.dataset = "ms1m-retinaface-t1"
config.embedding_size = 512
config.sample_rate = 1
config.fp16 = False
config.momentum = 0.9
config.weight_decay = 5e-4
config.batch_size = 128
config.lr = 0.1 # batch size is 512
if config.dataset == "emore":
config.rec = "/train_tmp/faces_emore"
config.num_classes = 85742
config.num_image = 5822653
config.num_epoch = 16
config.warmup_epoch = -1
config.decay_epoch = [8, 14, ]
config.val_targets = ["lfw", ]
elif config.dataset == "ms1m-retinaface-t1":
config.rec = "/train_tmp/ms1m-retinaface-t1"
config.num_classes = 93431
config.num_image = 5179510
config.num_epoch = 25
config.warmup_epoch = -1
config.decay_epoch = [11, 17, 22]
config.val_targets = ["lfw", "cfp_fp", "agedb_30"]
elif config.dataset == "glint360k":
config.rec = "/train_tmp/glint360k"
config.num_classes = 360232
config.num_image = 17091657
config.num_epoch = 20
config.warmup_epoch = -1
config.decay_epoch = [8, 12, 15, 18]
config.val_targets = ["lfw", "cfp_fp", "agedb_30"]
elif config.dataset == "webface":
config.rec = "/train_tmp/faces_webface_112x112"
config.num_classes = 10572
config.num_image = "forget"
config.num_epoch = 34
config.warmup_epoch = -1
config.decay_epoch = [20, 28, 32]
config.val_targets = ["lfw", "cfp_fp", "agedb_30"]
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