code: def test_sigmoid_focal_loss_with_logits():
      input_good = torch.tensor([10, -10, 10]).float()
      input_bad = torch.tensor([-1, 2, 0]).float()
      target = torch.tensor([1, 0, 1])
  
      loss_good = F.focal_loss_with_logits(input_good, target)
      loss_bad = F.focal_loss_with_logits(input_bad, target)
      assert loss_good < loss_bad
  
      loss_cls = BinaryFocalLoss()
      assert loss_cls(input_good, target) < loss_cls(input_bad, target)
  
imports: import numpy
  import pytest
  import pytorch_toolbelt.losses.functional
  import torch
  from pytorch_toolbelt import losses
  from torch import nn
  from pytorch_toolbelt.losses import BinaryFocalLoss, CrossEntropyFocalLoss
label_desc: Use image node_id 1 for calling a global function with example usage: test_sigmoid_focal_loss_with_logits() without return types