code: def test_reshape_method(self):
      arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]])
      arr_shape = arr.shape
  
      tgt = [[1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12]]
  
      # reshape(*shape_tuple)
      assert np.all(arr.reshape(2, 6) == tgt)
      assert (
          arr.reshape(2, 6).tensor._base is arr.tensor
      )  # reshape keeps the base
      assert arr.shape == arr_shape  # arr is intact
  
      # XXX: move out to dedicated test(s)
      assert arr.reshape(2, 6).tensor._base is arr.tensor
  
      # reshape(shape_tuple)
      assert np.all(arr.reshape((2, 6)) == tgt)
      assert arr.reshape((2, 6)).tensor._base is arr.tensor
      assert arr.shape == arr_shape
  
      tgt = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]
      assert np.all(arr.reshape(3, 4) == tgt)
      assert arr.reshape(3, 4).tensor._base is arr.tensor
      assert arr.shape == arr_shape
  
      assert np.all(arr.reshape((3, 4)) == tgt)
      assert arr.reshape((3, 4)).tensor._base is arr.tensor
      assert arr.shape == arr_shape
  
imports: import itertools
  from unittest import expectedFailure, skipIf
  import numpy
  import pytest
  from pytest import raises
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, run_tests, skipIfTorchDynamo, subtest, TEST_WITH_TORCHDYNAMO, TestCase, xpassIfTorchDynamo
label_desc: Use image node_id 2 for calling the TestReshape obj's underlying member method code with example usage: obj.test_reshape_method() without return types