How can I use 2 images as a training sample in PyTorch？
I just begin learning deep learning and my first homework is to finish an leaves-classification system based on convolutional neural networks.I built a resnet-34 model with the code on github to do it.However,my teacher told me that the basic training unit in his dataset is an image pair.I should use 2 images(photos of the same leaf under different light conditions) as the input,combining two 3-channel images into one 6-channel image,but I don't know how to input 2 images and combine them into 6 channels.How can I do that?Are there any functions?Should I modify the structure of the resnet network?

this is my dataset,you can see every two images are about the same leaf.

You have several issues to tackle:

You need a Dataset with a __getitem__ method that returns 2 images (and a label) instead of the basic ones that returns a single image and a label. You'll probably need to customize your own dataset.
Make sure the augmentations you apply to your images are applied in the same manner to each pair.
You need to modify ResNet-34 network to get as an input 2 images, instead of one. See, e.g., this answer how that can be done.
You need to change the first convolution layer to have 6 input channels instead of 3.
If you want to use pre-trained weights you will not be able to load the existing state_dict of ResNet34 because of changes #3 and #4 - you'll have to do it manually for the first time.

