code: def test_in_out(self):  # pylint: disable=no-self-use
      layer = BCELossMasked(pos_weight=5.0)
  
      length = T.tensor([95])
      target = (
          1.0 - sequence_mask(length - 1, 100).float()
      )  # [0, 0, .... 1, 1] where the first 1 is the last mel frame
      true_x = (
          target * 200 - 100
      )  # creates logits of [-100, -100, ... 100, 100] corresponding to target
      zero_x = (
          T.zeros(target.shape) - 100.0
      )  # simulate logits if it never stops decoding
      early_x = (
          -200.0 * sequence_mask(length - 3, 100).float() + 100.0
      )  # simulate logits on early stopping
      late_x = (
          -200.0 * sequence_mask(length + 1, 100).float() + 100.0
      )  # simulate logits on late stopping
  
      loss = layer(true_x, target, length)
      self.assertEqual(loss.item(), 0.0)
  
      loss = layer(early_x, target, length)
      self.assertAlmostEqual(loss.item(), 2.1053, places=4)
  
      loss = layer(late_x, target, length)
      self.assertAlmostEqual(loss.item(), 5.2632, places=4)
  
      loss = layer(zero_x, target, length)
      self.assertAlmostEqual(loss.item(), 5.2632, places=4)
  
      # pos_weight should be < 1 to penalize early stopping
      layer = BCELossMasked(pos_weight=0.2)
      loss = layer(true_x, target, length)
      self.assertEqual(loss.item(), 0.0)
  
      # when pos_weight < 1 overweight the early stopping loss
  
      loss_early = layer(early_x, target, length)
      loss_late = layer(late_x, target, length)
      self.assertGreater(loss_early.item(), loss_late.item())
  
file_path: TTS/tests/tts_tests/test_losses.py
imports: import unittest
  import torch
  from TTS.tts.layers.losses import BCELossMasked, L1LossMasked, MSELossMasked, SSIMLoss
  from TTS.tts.utils.helpers import sequence_mask
label_desc: Use image node_id 1 for calling the BCELossTest obj's underlying member method code with example usage: obj.test_in_out() without return types