code: def oasis_logits(request):
      shape = request.param
      rng = torch.Generator()
      rng.manual_seed(int(torch.prod(torch.tensor(shape))))
  
      target_shape = (shape[0],) + shape[2:]
  
      logits1 = torch.randn(size=shape, generator=rng)
      logits2 = torch.randn(size=shape, generator=rng)
      target = torch.randint(
          low=0, high=shape[1] - 1, size=target_shape
      )
  
      return logits1, logits2, target
  
imports: import pytest
  import torch
  import torch.nn.functional
  from neuralcompression.loss_fn import OASISDiscriminatorLoss, OASISGeneratorLoss
label_desc: Use image node_id 1 for calling a global function with example usage: oasis_logits(request) and returns: logits1,  logits2,  target