torchvision | R interface to torchvision | Machine Learning library

I am currently working on an neuronal network that can classify cats and dog and everything thats not cat nor dog. And my programm has this: error i can't solve:

" File "/home/johann/Schreibtisch/NN_v0.01/classification.py", line 146, in train(epoch) File "/home/johann/Schreibtisch/NN_v0.01/classification.py", line 109, in train loss = criterion(out, target) File "/home/johann/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "/home/johann/.local/lib/python3.8/site-packages/torch/nn/modules/loss.py", line 1047, in forward return F.cross_entropy(input, target, weight=self.weight, File "/home/johann/.local/lib/python3.8/site-packages/torch/nn/functional.py", line 2693, in cross_entropy return nll_loss(log_softmax(input, 1), target, weight, None, ignore_index, None, reduction) File "/home/johann/.local/lib/python3.8/site-packages/torch/nn/functional.py", line 2388, in nll_loss ret = torch._C._nn.nll_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index) RuntimeError: 1D target tensor expected, multi-target not supported"

The code:

I am trying to run the training of stylegan2-pytorch on a remote system. The remote system has gcc (9.3.0) installed on it. I'm using conda env that has the following installed (cudatoolkit=10.2, torch=1.5.0+, and ninja=1.8.2, gcc_linux-64=7.5.0). I encounter the following error:

Problem Description:

I am trying to load image data using Pytorch custom dataset. I did a little dive deep and found that my images set consist of 2 types of shape (512,512,3) and (1024,1024) . My assumption is, because of the above reason, it is throwing the below error.

Note: The code is able to read some of the images but, it is throwing the below error message for few of them. This was the reason to do a little EDA on the image data and found that there were 2 different shapes of images in the dataset.

Q1. How to preprocess such image data for training?

Q2. Is there any other reasons why I might be seeing the below error message?

Error message:

I have installed pytorch version 1.10.0 alongside torchtext, torchvision and torchaudio using conda. My PyTorch is cpu-only, and I have experimented with both conda install pytorch-mutex -c pytorch and conda install pytorch cpuonly -c pytorch to install the cpuonly version, both yielding the same eror that I will describe in the following lines.

I have also installed pytorch-lightning in conda, alongside jsonargparse[summaries via pip in the environment.

I have written this code to see whether LightningCLI works or not.

I'm trying to train my own object detection model with Pytorch. But im getting always this error. I tried to change the torch version but this doesn't helped.
My packages: torchvision-0.11.1 and torch-1.10.0

I am training a GANS on the Cifar-10 dataset in PyTorch (and hence don't need train/val/test splits), and I want to be able to combine the torchvision.datasets.CIFAR10 in the snippet below to form one single torch.utils.data.DataLoader iterator. My current solution is something like :

Recently I downloaded CelebA dataset from this page. I want to apply some transformations to this data set:

To do it firstly let's define transformations:

I've been trying to install PyTorch 1.9 with Cuda (ideally 11) on my HPC but I cannot.

The cluster says:

I have the following code: