You can for example run
>>> import torch

>>> tensor = torch.arange(6)
>>> array = tensor.numpy()

>>> tensor
tensor([0, 1, 2, 3, 4, 5])
>>> array
array([0, 1, 2, 3, 4, 5])

>>> tensor[0] = 10
>>> tensor
tensor([10,  1,  2,  3,  4,  5])
>>> array
array([10,  1,  2,  3,  4,  5])

>>> array[1] = -2
>>> tensor
tensor([10, -2,  2,  3,  4,  5])
>>> array
array([10, -2,  2,  3,  4,  5])

You can clearly see that both tensor and array share storage.