code: def test_in_out(self):
      embedding_dim = 64
      num_speakers = 5
      batch_size = 4
  
      dummy_label = T.randint(
          low=0, high=num_speakers, size=(batch_size, num_speakers)
      )
      # check random input
      dummy_input = T.rand(
          batch_size, num_speakers, embedding_dim
      )  # num_speaker x num_utterance x dim
      loss = SoftmaxAngleProtoLoss(
          embedding_dim=embedding_dim, n_speakers=num_speakers
      )
      output = loss.forward(dummy_input, dummy_label)
      assert output.item() >= 0.0
  
      # check all zeros
      dummy_input = T.ones(
          batch_size, num_speakers, embedding_dim
      )  # num_speaker x num_utterance x dim
      loss = SoftmaxAngleProtoLoss(
          embedding_dim=embedding_dim, n_speakers=num_speakers
      )
      output = loss.forward(dummy_input, dummy_label)
      assert output.item() >= 0.0
  
imports: import unittest
  import torch
  from tests import get_tests_input_path
  from TTS.encoder.losses import AngleProtoLoss, GE2ELoss, SoftmaxAngleProtoLoss
  from TTS.encoder.models.lstm import LSTMSpeakerEncoder
  from TTS.encoder.models.resnet import ResNetSpeakerEncoder
label_desc: Use image node_id 1 for calling the SoftmaxAngleProtoLossTests obj's underlying member method code with example usage: obj.test_in_out() without return types