I have a list of torch tensors, each is a tensor that holds predictions and i wish to average those. So, image 10982 predictions and we repeat that 3 times:
my_list =  for i in range(3): my_list.append(torch.arange(i,10982+i, dtype=torch.float32).reshape(10982,1))
is there a better way (a more pytorch or even numpy way) vs just doing list aggregate functions? It looks like the below is giving me what I want, it returns a tensor of size 10982,1 which is what I want. I just figured there is a more proper pytorch way of doing this.