code: def get_random_torch_batch(g, shapes, dtype):
      is_fp = torch.is_floating_point(torch.tensor([], dtype=dtype))
      if is_fp:
          return [
              torch.rand((shape), generator=g, dtype=dtype)
              for shape in shapes
          ]
      else:
          iinfo = torch.iinfo(dtype)
          dtype_min, dtype_max = iinfo.min, iinfo.max
          return [
              torch.randint(
                  dtype_min, dtype_max, shape, generator=g, dtype=dtype
              )
              for shape in shapes
          ]
  
imports: import numpy
  import nvidia.dali.ops
  import nvidia.dali.types
  import os
  import random
  from functools import partial
  from nvidia.dali.pipeline import Pipeline
  from nvidia.dali import fn, pipeline_def
  from nvidia.dali.python_function_plugin import current_dali_stream
label_desc: Use image node_id 33 for calling a global function with example usage: get_random_torch_batch(g, shapes, dtype) and returns: unknown, unknown