import torch.nn as nn
from vedaseg.utils import Registry
CRITERIA = Registry('criterion')
BCEWithLogitsLoss = nn.BCEWithLogitsLoss
CRITERIA.register_module(BCEWithLogitsLoss)
from vedaseg.utils import Registry
MODELS = Registry('model')
from vedaseg.utils import Registry
HEADS = Registry('head')
from vedaseg.utils import Registry
ENHANCE_MODULES = Registry('enhance_module')
from vedaseg.utils import Registry
import albumentations as albu
TRANSFORMS = Registry('transforms')
from vedaseg.utils import Registry
DATASETS = Registry('dataset')
from torch.optim import lr_scheduler
from vedaseg.utils import Registry
LR_SCHEDULERS = Registry('lr_scheduler')
MultiStepLR = lr_scheduler.MultiStepLR
LR_SCHEDULERS.register_module(MultiStepLR)
from vedaseg.utils import Registry
RUNNERS = Registry('runner')
from vedaseg.utils import Registry
BRICKS = Registry('brick')
DECODERS = Registry('decoder')
import torch.nn as nn
from vedaseg.utils import Registry
CRITERIA = Registry('criterion')
CrossEntropyLoss = nn.CrossEntropyLoss
CRITERIA.register_module(CrossEntropyLoss)
from vedaseg.utils import Registry
UTILS = Registry('utils')
from vedaseg.utils import Registry
BACKBONES = Registry('backbone')