import scheduler
# import torch.optim as optim
BATCH_SIZE = 128
N_WORKERS = 2
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 = resnet18_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 = ResNet.ResNet16()
FOLD = "resnet16_ssc"
import models.ResNet as ResNet
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 = ResNet.ResNet16(num_classes=100)
FOLD = "resnet16_cifar100_ssc"
