Reputation: 315
I have a problem converting a python list of numbers to pytorch Tensor :
this is my code :
caption_feat = [int(x) if x < 11660 else 3 for x in caption_feat]
printing caption_feat gives : [1, 9903, 7876, 9971, 2770, 2435, 10441, 9370, 2]
I do the converting like this : tmp2 = torch.Tensor(caption_feat)
now printing tmp2 gives : tensor([1.0000e+00, 9.9030e+03, 7.8760e+03, 9.9710e+03, 2.7700e+03, 2.4350e+03,
1.0441e+04, 9.3700e+03, 2.0000e+00])
However I expected to get : tensor([1. , 9903, , 9971. ......])
Any Idea?
Upvotes: 18
Views: 85769
Reputation: 211
You can directly convert python list
to a pytorch Tensor
by defining the dtype
. For example,
import torch
a_list = [3,23,53,32,53]
a_tensor = torch.Tensor(a_list)
print(a_tensor.int())
>>> tensor([3,23,53,32,53])
Upvotes: 20
Reputation: 357
A simple option is to convert your list to a numpy array, specify the dtype
you want and call torch.from_numpy
on your new array.
Toy example:
some_list = [1, 10, 100, 9999, 99999]
tensor = torch.from_numpy(np.array(some_list, dtype=np.int))
Another option as others have suggested is to specify the type when you create the tensor:
torch.tensor(some_list, dtype=torch.int)
Both should work fine.
Upvotes: 1
Reputation: 197
Try
torch.IntTensor(caption_feat)
You can see the other types here https://pytorch.org/docs/stable/tensors.html
Upvotes: 0
Reputation: 7693
If all elements are integer you can make integer torch tensor by defining dtype
>>> a_list = [1, 9903, 7876, 9971, 2770, 2435, 10441, 9370, 2]
>>> tmp2 = torch.tensor(a_list, dtype=torch.int)
>>> tmp2
tensor([ 1, 9903, 7876, 9971, 2770, 2435, 10441, 9370, 2],
dtype=torch.int32)
While torch.Tensor
returns torch.float32
which made it to print number in scientific notation
>>> tmp2 = torch.Tensor(a_list)
>>> tmp2
tensor([1.0000e+00, 9.9030e+03, 7.8760e+03, 9.9710e+03, 2.7700e+03, 2.4350e+03,
1.0441e+04, 9.3700e+03, 2.0000e+00])
>>> tmp2.dtype
torch.float32
Upvotes: 5