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DS-1000 / 975 / I have a logistic regression model using Pytorch, where my input is…

Problem

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Problem:

I have a logistic regression model using Pytorch, where my input is high-dimensional and my output must be a scalar - 0, 1 or 2.

I'm using a linear layer combined with a softmax layer to return a n x 3 tensor, where each column represents the probability of the input falling in one of the three classes (0, 1 or 2).

However, I must return a n x 1 tensor, so I need to somehow pick the highest probability for each input and create a tensor indicating which class had the highest probability. How can I achieve this using Pytorch?

To illustrate, my Softmax outputs this:

[[0.7, 0.2, 0.1],
 [0.2, 0.6, 0.2],
 [0.1, 0.1, 0.8]]
And I must return this:

[[0],
 [1],
 [2]]


A:

<code>
import numpy as np
import pandas as pd
import torch
softmax_output = load_data()
</code>
y = ... # put solution in this variable
BEGIN SOLUTION
<code>

library

Pytorch

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Source and history

upstream_id / Original problem ID
975
task_id
051847f6-0549-5b82-8cec-7954eae3b7f5
task_key
default--test--975
task_revision_id
1
config / split
default / test

Official source

initial import