code: def generate_code(self) -> Callable:
      # dst will be None since we don't ask for an allocation
      parallel_range = Compiler.get_iterator()
  
      def corrupt_fixed(labs, _, inds):
          for i in parallel_range(labs.shape[0]):
              # Because the random seed is tied to the image index, the
              # same images will be corrupted every epoch:
              np.random.seed(inds[i])
              if np.random.rand() < 0.2:
                  # They will also be corrupted to a deterministic label:
                  labs[i] = np.random.randint(low=0, high=10)
          return labs
  
      corrupt_fixed.is_parallel = True
      corrupt_fixed.with_indices = True
      return corrupt_fixed
  
file_path: ffcv/examples/docs_examples/transform_with_inds.py
imports: from dataclasses import replace
  import time
  from typing import Callable, Optional, Tuple
  import numpy
  import torchvision
  from ffcv.fields import IntField, RGBImageField
  from ffcv.fields.decoders import IntDecoder
  from ffcv.loader import Loader, OrderOption
  from ffcv.pipeline.compiler import Compiler
  from ffcv.pipeline.operation import Operation, AllocationQuery
  from ffcv.pipeline.state import State
  from ffcv.transforms import ToTensor
  from ffcv.writer import DatasetWriter
label_desc: Use image node_id 1 for calling the CorruptFixedLabels obj's underlying member method code with example usage: obj.generate_code() and returns: corrupt_fixed, labs