code: def _tensor_arg_rotate_params():
      batch_sizes = [3, 1, 2, 4]
      mask_batches = [
          np.array([i % 2 for i in range(batch_size)], dtype=bool)
          for batch_size in batch_sizes
      ]
      kwarg_batches = [
          np.array([10 + 45 * pred for pred in mask], dtype=np.float32)
          for mask in mask_batches
      ]
      return tuple(), mask_batches, {"angle": kwarg_batches}
  
imports: from nvidia.dali.pipeline import pipeline_def, experimental
  import nvidia.dali.fn
  import nvidia.dali.types
  from nvidia.dali.types import SampleInfo
  from nvidia.dali import _conditionals
  from nvidia.dali.data_node import DataNode
  import numpy
  import os
  from test_utils import check_batch, compare_pipelines
  from nose_utils import assert_raises
  from test_utils import get_dali_extra_path
  from nose2.tools import params
  import itertools
label_desc: Use image node_id 35 for calling a global function with example usage: _tensor_arg_rotate_params() and returns: tuple,  mask_batches,  dict