code: def prepare_parameters(nntxt_str):
      proto = proto_from_str(nntxt_str)
      proto = NnpExpander(proto).execute()
      rng = np.random.RandomState(0)
      for n in proto.network:
          for v in n.variable:
              shape = tuple(
                  [d if d >= 1 else n.batch_size for d in v.shape.dim]
              )
              variable = _create_variable(v, v.name, shape, rng)
  
imports: import os
  import io
  import pytest
  import numpy
  import nnabla
  import nnabla.functions
  from nnabla.testing import assert_allclose
  from contextlib import contextmanager
  from shutil import rmtree
  import tempfile
  import numpy
  import warnings
  from legacy_expander import NnpExpander
  from nnabla.utils import nnabla_pb2
  from legacy_load import _create_variable
  import google.protobuf.text_format
  from nnabla.utils.image_utils import imsave
  from nnabla.utils.get_file_handle import get_file_handle_save
  from nnabla.utils.nnp_format import nnp_version
label_desc: Use image node_id 11 for calling a global function with example usage: prepare_parameters(nntxt_str) without return types