code: def test_binary_bi_tempered_loss():
      loss = L.BinaryBiTemperedLogisticLoss(
          t1=0.9, t2=3.0, ignore_index=-100
      )
  
      y_pred = torch.randn((4, 1, 512, 512))
      y_true = (y_pred > 0).type_as(y_pred)
      y_true[:, :, ::10, ::20] = -100
      loss_value = loss(y_pred, y_true)
      assert len(loss_value.size()) == 0
  
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 13 for calling a global function with example usage: test_binary_bi_tempered_loss() without return types