code: def test_ctor_with_invalid_numpy_array_sequence(self, device):
      # Invalid list of numpy array
      with self.assertRaisesRegex(
          ValueError, "expected sequence of length"
      ):
          torch.tensor(
              [
                  np.random.random(size=(3, 3)),
                  np.random.random(size=(3, 0)),
              ],
              device=device,
          )
  
      # Invalid list of list of numpy array
      with self.assertRaisesRegex(
          ValueError, "expected sequence of length"
      ):
          torch.tensor(
              [
                  [
                      np.random.random(size=(3, 3)),
                      np.random.random(size=(3, 2)),
                  ]
              ],
              device=device,
          )
  
      with self.assertRaisesRegex(
          ValueError, "expected sequence of length"
      ):
          torch.tensor(
              [
                  [
                      np.random.random(size=(3, 3)),
                      np.random.random(size=(3, 3)),
                  ],
                  [
                      np.random.random(size=(3, 3)),
                      np.random.random(size=(3, 2)),
                  ],
              ],
              device=device,
          )
  
      # expected shape is `[1, 2, 3]`, hence we try to iterate over 0-D array
      # leading to type error : not a sequence.
      with self.assertRaisesRegex(TypeError, "not a sequence"):
          torch.tensor(
              [[np.random.random(size=(3)), np.random.random()]],
              device=device,
          )
  
      # list of list or numpy array.
      with self.assertRaisesRegex(
          ValueError, "expected sequence of length"
      ):
          torch.tensor(
              [
                  [1, 2, 3],
                  np.random.random(size=(2,)),
              ],
              device=device,
          )
  
imports: import torch
  import numpy
  from itertools import product
  from torch.testing._internal.common_utils import skipIfTorchDynamo, TestCase, run_tests
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, onlyCPU, dtypes, skipMeta
  from torch.testing._internal.common_dtype import all_types_and_complex_and
label_desc: Use image node_id 8 for calling the TestNumPyInterop obj's underlying member method code with example usage: obj.test_ctor_with_invalid_numpy_array_sequence(device) without return types