code: def test_nnp_graph_reshape(
      tmpdir, variable_batch_size, batch_size, shape
  ):
      x = nn.Variable([10, 2, 10, 10])
      h = PF.convolution(x, 4, kernel=(3, 3), stride=(1, 1))
      y = F.reshape(h, shape=shape)
      x2, y2 = check_nnp_graph_save_load(
          tmpdir, x, y, batch_size, variable_batch_size
      )
      if not variable_batch_size:
          return
      shape2 = list(y.shape)
      shape2[0] = batch_size
      x2.d = np.random.randn(*x2.shape)
      y2.forward()
  
imports: import pytest
  import numpy
  import nnabla
  import nnabla.functions
  import nnabla.parametric_functions
  from nnabla.testing import assert_allclose
  from helper import get_saved_test_model, forward_variable_and_check_equal, forward_variable, assert_topology, dump_network_topology
  import legacy_nnp_graph
  from nnabla.utils import nnp_graph
label_desc: Use image node_id 22 for calling a global function with example usage: test_nnp_graph_reshape(tmpdir, variable_batch_size, batch_size, shape) without return types