Checking trained CNN on the images I trained my CNN (model) classifier and want to check it on some new images. I have image x, so this syntax works for me for one image:
torch.argmax(model(x))

What if I want to classify 2 more images (different classes),  let's say images y and z? Should I for every image write a new line or is it possible to put in the code above 3 together?
torch.argmax has an extra argument dim which you can specify such that the maximum value is taken over a specific dimension. If you specify the dimension which represents the number of images it will return an array of indices where each value is for one image. For example:
import torch

# 3 images with 5 classes
t = torch.randn(3, 5)

# tensor([[-1.2917,  1.3740,  0.6967, -0.0575,  0.3702],
#        [ 0.5428,  1.0863,  0.3951,  1.8535,  1.0926],
#        [ 0.5865,  0.8522, -0.6858,  0.5297, -0.1320]])

# get the argmax over the first dimension, which specifies the number of images
torch.argmax(t, dim=1)

# tensor([1, 3, 1])