PyTorch: How to get the shape of a Tensor as a list of int

For PyTorch v1.0 and possibly above:

>>> import torch
>>> var = torch.tensor([[1,0], [0,1]])

# Using .size function, returns a torch.Size object.
>>> var.size()
torch.Size([2, 2])
>>> type(var.size())
<class 'torch.Size'>

# Similarly, using .shape
>>> var.shape
torch.Size([2, 2])
>>> type(var.shape)
<class 'torch.Size'>

You can cast any torch.Size object to a native Python list:

>>> list(var.size())
[2, 2]
>>> type(list(var.size()))
<class 'list'>

---

In PyTorch v0.3 and 0.4:

Simply list(var.size()), e.g.:

>>> import torch
>>> from torch.autograd import Variable
>>> from torch import IntTensor
>>> var = Variable(IntTensor([[1,0],[0,1]]))

>>> var
Variable containing:
 1  0
 0  1
[torch.IntTensor of size 2x2]

>>> var.size()
torch.Size([2, 2])

>>> list(var.size())
[2, 2]

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.