code: def test_rn50_ops_pipe():
      @pipeline_def(batch_size=10, device_id=0, num_threads=4)
      def rn50_ops_pipe():
          Reader = ops.readers.File(
              files=[
                  str(
                      _test_root
                      / "db/single/jpeg/113/snail-4291306_1280.jpg"
                  )
              ],
              name="FileReader",
          )
          Decoder = ops.decoders.Image(device="mixed")
          Rng = ops.random.CoinFlip(probability=0.5)
          Rrc = ops.RandomResizedCrop(device="gpu", size=[224, 224])
          Cmn = ops.CropMirrorNormalize(
              mirror=Rng(),
              device="gpu",
              dtype=types.DALIDataType.FLOAT16,
              output_layout="HWC",
              crop=(224, 224),
              mean=[0.485 * 255, 0.456 * 255, 0.406 * 255],
              std=[0.229 * 255, 0.224 * 255, 0.225 * 255],
          )
          enc, label = Reader()
          imgs = Decoder(enc)
          resized = Rrc(imgs)
          normalized = Cmn(resized)
          expect_data_node(
              enc, label, imgs, resized, normalized, label.gpu()
          )
          return normalized, label.gpu()
  
      pipe = rn50_ops_pipe()
      expect_pipeline(pipe)
      pipe.build()
      imgs, labels = pipe.run()
      expect_tensor_list(imgs, labels)
      assert isinstance(imgs, tensors.TensorListGPU)
      assert imgs.dtype == types.DALIDataType.FLOAT16  # noqa: E721
      assert isinstance(labels, tensors.TensorListGPU)
  
imports: from pathlib import Path
  import numpy
  from typing import cast, Sequence, Union
  from nvidia.dali import fn, ops
  from nvidia.dali import types, tensors
  from nvidia.dali.data_node import DataNode
  from nvidia.dali.pipeline import pipeline_def, Pipeline
  from test_utils import get_dali_extra_path, check_numba_compatibility_cpu
  from nose.plugins.attrib import attr
label_desc: Use image node_id 6 for calling a global function with example usage: test_rn50_ops_pipe() and returns: normalized,  label