In numpy, V.shape
gives a tuple of ints of dimensions of V.
In tensorflow V.get_shape().as_list()
gives a list of integers of the dimensions of
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]
Previous answers got you list of torch.Size Here is how to get list of ints
listofints = [int(x) for x in tensor.shape]
If you're a fan of NumPy
ish 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.