If you're a fan of NumPyish syntax, then there's tensor.shape.
In [3]: ar = torch.rand(3, 3)
In [4]: ar.shape
Out[4]: torch.Size([3, 3])
# method-1
In [7]: list(ar.shape)
Out[7]: [3, 3]
# method-2
In [8]: [*ar.shape]
Out[8]: [3, 3]
# method-3
In [9]: [*ar.size()]
Out[9]: [3, 3]
P.S.: Note that tensor.shape is an alias to tensor.size(), though tensor.shape is an attribute of the tensor in question whereas tensor.size() is a function.