code: def _test_scalar_shape(dtype, shape, layout):
      def sample_source(sample_info):
          sample_size = np.prod(shape)
          x = sample_info.idx_in_epoch + 1
          sample = (
              np.arange(0, sample_size, dtype=dtype).reshape(shape) * x
          )
          return sample
  
      def deflated_source(sample_info):
          sample = sample_source(sample_info)
          return np.array(sample_to_lz4(sample))
  
      @pipeline_def
      def pipeline():
          baseline = fn.external_source(
              source=sample_source, batch=False
          )
          deflated = fn.external_source(
              source=deflated_source, batch=False, device="gpu"
          )
          inflated = fn.experimental.inflate(
              deflated,
              shape=shape,
              dtype=np_type_to_dali(dtype),
              layout=layout,
          )
          return inflated, baseline
  
      batch_size = 16
      pipe = pipeline(batch_size=batch_size, num_threads=8, device_id=0)
      pipe.build()
      for _ in range(4):
          inflated, baseline = pipe.run()
          check_batch(inflated, baseline, batch_size, layout)
  
file_path: DALI/dali/test/python/operator_1/test_inflate.py
imports: import numpy
  from nvidia.dali import pipeline_def, fn, types
  from test_utils import np_type_to_dali, has_operator, restrict_platform
  from nose_utils import assert_raises
  from nose2.tools import params
label_desc: Use image node_id 5 for calling a global function with example usage: _test_scalar_shape(dtype, shape, layout) and returns: sample, np, inflated,  baseline