class_docstr: Randomly choose one of the best 25 Sub-policies on CIFAR10.
  Example:
  >>> policy = CIFAR10Policy()
  >>> transformed = policy(image)
  Example as a PyTorch Transform:
  >>> transform=transforms.Compose([
  >>>     transforms.Resize(256),
  >>>     CIFAR10Policy(),
  >>>     transforms.ToTensor()])
class_docstr_tok: ["Randomly","choose","one","of","the","best","25","Sub-policies","on","CIFAR10",".","Example",":",">",">",">","policy","=","CIFAR10Policy","(",")",">",">",">","transformed","=","policy","(","image",")","Example","as","a","PyTorch","Transform",":",">",">",">","transform=transforms.Compose","(","[",">",">",">","transforms.Resize","(","256",")",",",">",">",">","CIFAR10Policy","(",")",",",">",">",">","transforms.ToTensor","(",")","]",")"]
code: def __init__(self, fillcolor=(128, 128, 128)):
      self.policies = [
          SubPolicy(0.1, "invert", 7, 0.2, "contrast", 6, fillcolor),
          SubPolicy(0.7, "rotate", 2, 0.3, "translateX", 9, fillcolor),
          SubPolicy(
              0.8, "sharpness", 1, 0.9, "sharpness", 3, fillcolor
          ),
          SubPolicy(0.5, "shearY", 8, 0.7, "translateY", 9, fillcolor),
          SubPolicy(
              0.5, "autocontrast", 8, 0.9, "equalize", 2, fillcolor
          ),
          SubPolicy(0.2, "shearY", 7, 0.3, "posterize", 7, fillcolor),
          SubPolicy(0.4, "color", 3, 0.6, "brightness", 7, fillcolor),
          SubPolicy(
              0.3, "sharpness", 9, 0.7, "brightness", 9, fillcolor
          ),
          SubPolicy(0.6, "equalize", 5, 0.5, "equalize", 1, fillcolor),
          SubPolicy(0.6, "contrast", 7, 0.6, "sharpness", 5, fillcolor),
          SubPolicy(0.7, "color", 7, 0.5, "translateX", 8, fillcolor),
          SubPolicy(
              0.3, "equalize", 7, 0.4, "autocontrast", 8, fillcolor
          ),
          SubPolicy(
              0.4, "translateY", 3, 0.2, "sharpness", 6, fillcolor
          ),
          SubPolicy(0.9, "brightness", 6, 0.2, "color", 8, fillcolor),
          SubPolicy(0.5, "solarize", 2, 0.0, "invert", 3, fillcolor),
          SubPolicy(
              0.2, "equalize", 0, 0.6, "autocontrast", 0, fillcolor
          ),
          SubPolicy(0.2, "equalize", 8, 0.6, "equalize", 4, fillcolor),
          SubPolicy(0.9, "color", 9, 0.6, "equalize", 6, fillcolor),
          SubPolicy(
              0.8, "autocontrast", 4, 0.2, "solarize", 8, fillcolor
          ),
          SubPolicy(0.1, "brightness", 3, 0.7, "color", 0, fillcolor),
          SubPolicy(
              0.4, "solarize", 5, 0.9, "autocontrast", 3, fillcolor
          ),
          SubPolicy(
              0.9, "translateY", 9, 0.7, "translateY", 9, fillcolor
          ),
          SubPolicy(
              0.9, "autocontrast", 2, 0.8, "solarize", 3, fillcolor
          ),
          SubPolicy(0.8, "equalize", 8, 0.1, "invert", 3, fillcolor),
          SubPolicy(
              0.7, "translateY", 9, 0.9, "autocontrast", 1, fillcolor
          ),
      ]
  
imports: import math
  import random
  import numpy
  import torch
  import torch.distributed
  from PIL import Image, ImageEnhance, ImageOps
  from torch.utils.data import Sampler
label_desc: Use image node_id 1 to create a new CIFAR10Policy object from inherited base classes: object with example: obj = CIFAR10Policy(fillcolor)