From a 2D tensor, return a 1D tensor by selecting 1 column per row

Question

I have a 2D tensor and a 1D tensor:

import torch
torch.manual_seed(0)

out = torch.randn((16,2))
target = torch.tensor([0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0])

For each row of out, I want to select the corresponding column as indexed by target. Thus, my output will be a (16,1) tensor. I tried the solution mentioned here:

https://stackoverflow.com/a/58937071

But I get:

Traceback (most recent call last):
  File "/opt/conda/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3369, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-7-50d103c3b56c>", line 1, in <cell line: 1>
    out.gather(1, target)
RuntimeError: Index tensor must have the same number of dimensions as input tensor

Can you help?

Asked By: DeltaIV

||

Source

Answer 1

In order to apply torch.gather, the two tensors must have the same number of dimensions. As such you should unsqueeze an additional dimension on target in last position:

>>> out.gather(1, target[:,None])
tensor([[-1.1258],
        [-0.4339],
        [ 0.6920],
        [-2.1152],
        [ 0.3223],
        [ 0.3500],
        [ 1.2377],
        [ 1.1168],
        [-1.6959],
        [ 0.7935],
        [ 0.5988],
        [-0.3414],
        [ 0.7502],
        [ 0.1835],
        [ 1.5863],
        [ 0.9463]])

Answered By: Ivan

From a 2D tensor, return a 1D tensor by selecting 1 column per row

Question:

Answers: