code: def __init__(
      self,
      gaussian_blur_prob: float = 0.5,
      gaussian_blur_kernel_size: Optional[float] = None,
      gaussian_blur_sigmas: Tuple[float, float] = (0.1, 2),
      solarize_prob: float = 0.0,
      cj_prob: float = 1.0,
      cj_strength: float = 0.5,
      cj_bright: float = 0.8,
      cj_contrast: float = 0.8,
      cj_sat: float = 0.4,
      cj_hue: float = 0.2,
      random_gray_scale: float = 0.2,
      normalize: Union[
          None, Dict[str, List[float]]
      ] = IMAGENET_NORMALIZE,
  ):
      color_jitter = T.ColorJitter(
          brightness=cj_strength * cj_bright,
          contrast=cj_strength * cj_contrast,
          saturation=cj_strength * cj_sat,
          hue=cj_strength * cj_hue,
      )
  
      transforms = [
          T.RandomApply([color_jitter], p=cj_prob),
          T.RandomGrayscale(p=random_gray_scale),
          GaussianBlur(
              kernel_size=gaussian_blur_kernel_size,
              prob=gaussian_blur_prob,
              sigmas=gaussian_blur_sigmas,
          ),
          RandomSolarization(prob=solarize_prob),
          T.ToTensor(),
      ]
      if normalize:
          transforms += [
              T.Normalize(mean=normalize["mean"], std=normalize["std"])
          ]
      self.transform = T.Compose(transforms=transforms)
  
file_path: lightly/lightly/transforms/vicregl_transform.py
imports: from typing import Dict, List, Optional, Tuple, Union
  import torchvision.transforms
  from PIL.Image import Image
  from torch import Tensor
  from lightly.transforms.gaussian_blur import GaussianBlur
  from lightly.transforms.image_grid_transform import ImageGridTransform
  from lightly.transforms.random_crop_and_flip_with_grid import RandomResizedCropAndFlip
  from lightly.transforms.solarize import RandomSolarization
  from lightly.transforms.utils import IMAGENET_NORMALIZE
label_desc: Use image node_id 1 to create a new VICRegLViewTransform object  with example: obj = VICRegLViewTransform(gaussian_blur_prob, gaussian_blur_kernel_size, gaussian_blur_sigmas, solarize_prob, cj_prob, cj_strength, cj_bright, cj_contrast, cj_sat, cj_hue, random_gray_scale, normalize)