new_contents: import numpy as np
  
  def test_array_reshape_to_dims():
      from research_pyutils import array_reshape_to_dims
      a = np.array([[1, 2], [3, 4], [5, 6], [7, 8]])
      sh = a.shape
      tot = sh[0] * sh[1]
  
      # # test 1 for a conversion, vectorize.
      b = array_reshape_to_dims(a, k=1)
      assert b.shape[0] == tot
      assert b[0] == a[0, 0] and b[-1] == a[-1, -1]
      assert np.all(b.reshape(sh) == a)
  
      # # test 2: convert to particular shape.
      b = array_reshape_to_dims(b, sh[1], sh[0], k=2)
      assert b.shape[0] == sh[1] and  b.shape[1] == sh[0]
      assert np.all(b.flatten().reshape(sh) == a)
      assert len(b.shape) == 2
  
      # # test 3: convert to particular shape.
      b = array_reshape_to_dims(b, sh[1], sh[0], k=3)
      assert b.shape[0] == sh[1] and  b.shape[1] == sh[0]
      assert np.all(b.flatten().reshape(sh) == a)
      assert len(b.shape) == 3
  
      # # test 4: convert to particular shape.
      b = array_reshape_to_dims(b, 1, tot)
      assert b.shape[1] == tot and b.shape[0] == 1
      assert np.all(b.flatten().reshape(sh) == a)
      assert len(b.shape) == 2
  
      # # reshape the original matrix a.
      a = a.reshape((2, 2, 2))
      sh = a.shape
  
      # # test 5: convert to particular shape.
      b = array_reshape_to_dims(b, 1, tot)
      assert b.shape[1] == tot and b.shape[0] == 1
      assert np.all(b.flatten().reshape(sh) == a)
      assert len(b.shape) == 2
  
      # # test 6 for a conversion, vectorize.
      b = array_reshape_to_dims(a, k=1)
      assert b.shape[0] == tot
      assert b[0] == a[0, 0, 0] and b[-1] == a[-1, -1, -1]
      assert np.all(b.reshape(sh) == a)
  
  
subject: Add the tests for auxiliary.py modules.