code: def __init__(self, batch_size, num_threads, device_id):
      super().__init__(batch_size, num_threads, device_id)
  
      self.decode = ops.decoders.Image(
          device="mixed", output_type=types.RGB
      )
      self.resize = ops.Resize(
          device="gpu", interp_type=types.INTERP_LINEAR
      )
      self.cmn = ops.CropMirrorNormalize(
          device="gpu",
          output_dtype=types.FLOAT,
          crop=(227, 227),
          mean=[128.0, 128.0, 128.0],
          std=[1.0, 1.0, 1.0],
      )
      self.uniform = ops.random.Uniform(range=(0.0, 1.0))
      self.resize_rng = ops.random.Uniform(range=(256, 480))
  
imports: import numpy
  import nvidia.dali.ops
  import nvidia.dali.plugin.tf
  import nvidia.dali.types
  import os.path
  import tensorflow
  from nvidia.dali.pipeline import Pipeline
  from nose_utils import raises
  from test_utils import get_dali_extra_path
label_desc: Use image node_id 1 to create a new CommonPipeline object from inherited base classes: Pipeline with example: obj = CommonPipeline(batch_size, num_threads, device_id)