code: def test_chunks():
      seed = 42
      batch_sizes = [1, 9, 31]
      for dtype in [np.uint8, np.int16, np.float32]:
          for ndim, layout, sequence_axis_name in [
              (0, None, None),
              (1, None, "F"),
              (2, "XY", "Q"),
              (2, None, None),
              (3, "ABC", None),
              (3, "", "W"),
          ]:
              for mode, permute in [
                  ("offset_only", False),
                  ("size_only", False),
                  ("offset_and_size", False),
                  ("offset_and_size", True),
              ]:
                  batch_size = batch_sizes[seed % len(batch_sizes)]
                  oversized_shape = ndim > 0 and seed % 2 == 1
                  yield (
                      _test_chunks,
                      seed,
                      batch_size,
                      ndim,
                      dtype,
                      layout,
                      mode,
                      permute,
                      oversized_shape,
                      sequence_axis_name,
                  )
                  seed += 1
  
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 9 for calling a global function with example usage: test_chunks() without return types