text: import logging
  from torchvision.transforms import (
          RandomHorizontalFlip,
          RandomRotation,
          RandomResizedCrop,
          ColorJitter,
          RandomGrayscale,
          RandomChoice,
          Compose,
          Normalize,
          ToTensor
  )
  from augmentations.augmentations import (
          RandomRotate90,
          ColorJitterSimCLR,
          GaussianDequantize,
          UniformDequantize,
          ToGray,
          Reweight,
          GaussianFilter,
          MinMaxScaler,
  )
  
  logger = logging.getLogger("ptsemseg")
  
  
  key2aug = {
          'hflip': RandomHorizontalFlip,
          'rotate': RandomRotate90,
          'rcrop': RandomResizedCrop,
          'cjitter': ColorJitterSimCLR,
          'rgray': RandomGrayscale,
          'GaussianDequantize': GaussianDequantize,
          'UniformDequantize': UniformDequantize,
          'togray': ToGray,
          'normalize': Normalize,
          'totensor': ToTensor,
          'Reweight': Reweight,
          'GaussianFilter': GaussianFilter,
          'MinMaxScaler': MinMaxScaler,
          }
  
  
  def get_composed_augmentations(aug_dict):
      if aug_dict is None:
          # print("Using No Augmentations")
          return None
  
      augmentations = []
      for aug_key, aug_param in aug_dict.items():
          augmentations.append(key2aug[aug_key](**aug_param))
          # print("Using {} aug with params {}".format(aug_key, aug_param))
      return Compose(augmentations)
  