code: def _testimpl_numpy_reader_roi(
      file_root,
      batch_size,
      ndim,
      dtype,
      device,
      fortran_order=False,
      file_filter="*.npy",
      roi_start=None,
      rel_roi_start=None,
      roi_end=None,
      rel_roi_end=None,
      roi_shape=None,
      rel_roi_shape=None,
      roi_axes=None,
      out_of_bounds_policy=None,
      fill_value=None,
  ):
      default_axes = list(range(ndim))
      pipe = numpy_reader_roi_pipe(
          file_root=file_root,
          file_filter=file_filter,
          device=device,
          roi_start=roi_start,
          rel_roi_start=rel_roi_start,
          roi_end=roi_end,
          rel_roi_end=rel_roi_end,
          roi_shape=roi_shape,
          rel_roi_shape=rel_roi_shape,
          roi_axes=roi_axes,
          default_axes=default_axes,
          out_of_bounds_policy=out_of_bounds_policy,
          fill_value=fill_value,
          batch_size=batch_size,
      )
  
      try:
          pipe.build()
          roi_out, sliced_out = pipe.run()
          for i in range(batch_size):
              roi_arr = to_array(roi_out[i])
              sliced_arr = to_array(sliced_out[i])
              assert_array_equal(roi_arr, sliced_arr)
      finally:
          del pipe
  
imports: from nvidia.dali import Pipeline, pipeline_def
  import nvidia.dali.fn
  import nvidia.dali.types
  import nvidia.dali.backend
  import numpy
  from numpy.testing import assert_array_equal
  import os
  import platform
  import random
  import tempfile
  from nose_utils import assert_raises
  from nose import SkipTest
  from nose2.tools import params, cartesian_params
  from test_utils import compare_pipelines, to_array
label_desc: Use image node_id 21 for calling a global function with example usage: _testimpl_numpy_reader_roi(file_root, batch_size, ndim, dtype, device, fortran_order, file_filter, roi_start, rel_roi_start, roi_end, rel_roi_end, roi_shape, rel_roi_shape, roi_axes, out_of_bounds_policy, fill_value) without return types