code: def test_batch_ifft_complex64_to_float32_2d(self):
      # Note that since rfftn returns a Fortran-ordered array, it
      # needs to be reformatted as a C-ordered array before being
      # passed to gpuarray.to_gpu:
      x = np.asarray(np.random.rand(self.B, self.N, self.M), np.float32)
      xf = np.asarray(np.fft.rfftn(x, axes=(1, 2)), np.complex64)
      xf_gpu = gpuarray.to_gpu(np.ascontiguousarray(xf))
      x_gpu = gpuarray.empty((self.B, self.N, self.M), np.float32)
      plan = fft.Plan(
          [self.N, self.M], np.complex64, np.float32, batch=self.B
      )
      fft.ifft(xf_gpu, x_gpu, plan, True)
      np.testing.assert_allclose(x, x_gpu.get(), atol=atol_float32)
  
imports: from __future__ import division
  from unittest import main, makeSuite, TestCase, TestSuite
  import pycuda.driver
  import pycuda.gpuarray
  from pycuda.tools import clear_context_caches, make_default_context
  import pycuda.gpuarray
  import numpy
  import skcuda.fft
  import skcuda.misc
label_desc: Use image node_id 15 for calling the test_fft obj's underlying member method code with example usage: obj.test_batch_ifft_complex64_to_float32_2d() without return types