code: def __init__(self, function, device, num_outputs=1):
      super(PythonFunctionPipeline, self).__init__(
          BATCH_SIZE, NUM_WORKERS, DEVICE_ID, seed=SEED
      )
      self.device = device
      self.reader = ops.readers.File(file_root=images_dir)
      self.decode = ops.decoders.Image(
          device="cpu", output_type=types.RGB
      )
      self.norm = ops.CropMirrorNormalize(
          std=255.0, mean=0.0, device=device, output_layout="HWC"
      )
      self.func = ops.PythonFunction(
          device=device, function=function, num_outputs=num_outputs
      )
  
file_path: DALI/dali/test/python/test_gpu_python_function_operator.py
imports: import cupy
  from nvidia.dali.pipeline import Pipeline
  import nvidia.dali.ops
  import nvidia.dali.types
  import numpy
  import test_utils
  import random
  import os
label_desc: Use image node_id 1 to create a new PythonFunctionPipeline object from inherited base classes: Pipeline with example: obj = PythonFunctionPipeline(function, device, num_outputs)