class_docstr: Apply Random color distortions to the input image.
  There are multiple different ways of applying these distortions.
  This implementation follows SimCLR - https://arxiv.org/abs/2002.05709
  It randomly distorts the hue, saturation, brightness of an image and can
  randomly convert the image to grayscale.
docstr: Args:
      strength (float): quantify the strength of the color distortion
      brightness (float): default brightness then multiplied by strength
      contrast (float): default contrast then multiplied by strength
      saturation (float): default saturation then multiplied by strength
      hue (float): default hue then multiplied by strength
code: def __init__(
      self,
      strength: float = 1.0,
      brightness: float = 0.8,
      contrast: float = 0.8,
      saturation: float = 0.8,
      hue: float = 0.2,
  ):
      """
      Args:
          strength (float): quantify the strength of the color distortion
          brightness (float): default brightness then multiplied by strength
          contrast (float): default contrast then multiplied by strength
          saturation (float): default saturation then multiplied by strength
          hue (float): default hue then multiplied by strength
      """
      self.strength = strength
      self.color_jitter = pth_transforms.ColorJitter(
          brightness=brightness * self.strength,
          contrast=contrast * self.strength,
          saturation=saturation * self.strength,
          hue=hue * self.strength,
      )
      self.rnd_color_jitter = pth_transforms.RandomApply(
          [self.color_jitter], p=0.8
      )
      self.rnd_gray = pth_transforms.RandomGrayscale(p=0.2)
      self.transforms = pth_transforms.Compose(
          [self.rnd_color_jitter, self.rnd_gray]
      )
  
file_path: vissl/vissl/data/ssl_transforms/img_pil_color_distortion.py
imports: import logging
  from typing import Any, Dict
  import torchvision.transforms
  from classy_vision.dataset.transforms import register_transform
  from classy_vision.dataset.transforms.classy_transform import ClassyTransform
label_desc: Use image node_id 1 to create a new ImgPilColorDistortion object from inherited base classes: ClassyTransform with example: obj = ImgPilColorDistortion(strength, brightness, contrast, saturation, hue)