import scheduler import torch.optim as optim BATCH_SIZE = 128 N_WORKERS = 4 EPOCHS = 300 #PATIENCE = 30 # PATIENCE = 5 PATIENCE = -1 LR = 0.1 W_DECAY = 5e-4 #2e-4 MOMENTUM = 0.9 #0.9 # LRS = [1,0.1, 0.01, 0.001, 0.0001] # fold = revnet18_morelr # LRS = [0.0001, 0.001, 0.01, 0.1, 0.01, 0.001, 0.0001] LRS = [0.1, 0.02, 0.004, 0.0008] LR_EPOCH = [60, 120, 160, 200] def SCHEDULER(optimizer): #return scheduler.MoreSimpleScheduler(optimizer, LRS) return scheduler.SimpleScheduler(optimizer, LR_EPOCH, LRS) # return optim.lr_scheduler.CosineAnnealingLR(optimizer, 12, eta_min=0, last_epoch=-1) MODEL = RevNet.RevNet18() FOLD = "revnet18_callr"
import models.RevNet as RevNet import os os.environ["CUDA_VISIBLE_DEVICES"] = '3' import scheduler BATCH_SIZE = 128 N_WORKERS = 4 EPOCHS = 300 PATIENCE = -1 LR = 0.1 W_DECAY = 5e-4#2e-4 MOMENTUM = 0.9#0.9 LRS = [0.1, 0.02, 0.004, 0.0008] LR_EPOCH = [60, 120, 160, 200] def SCHEDULER(optimizer): return scheduler.SimpleScheduler(optimizer, LR_EPOCH, LRS) MODEL = RevNet.RevNet18(num_classes=100) FOLD = "revnet18_cifar100"