code: def test_multiple_inputs_single_target(
      self, batch_size: int, target_count: int, input_count: int
  ):
      torch.random.manual_seed(0)
      logits = [
          torch.randn(size=(batch_size, target_count))
          for _ in range(input_count)
      ]
      target = torch.randint(0, target_count, size=(batch_size,))
  
      ref_criterion = nn.CrossEntropyLoss()
      ref_loss = sum(
          ref_criterion(logits[i], target) for i in range(input_count)
      )
      criterion = CrossEntropyMultipleOutputSingleTargetCriterion()
      self.assertEqual(criterion(logits, target), ref_loss)
  
imports: import logging
  import unittest
  from collections import namedtuple
  import torch
  import torch.nn
  import torch.optim
  from classy_vision.generic.distributed_util import set_cpu_device
  from parameterized import param, parameterized
  from vissl.config.attr_dict import AttrDict
  from vissl.losses.barlow_twins_loss import BarlowTwinsCriterion
  from vissl.losses.cross_entropy_multiple_output_single_target import CrossEntropyMultipleOutputSingleTargetCriterion, CrossEntropyMultipleOutputSingleTargetLoss
  from vissl.losses.distillation_loss import DistillationCriterion, DistillationLoss
  from vissl.losses.multicrop_simclr_info_nce_loss import MultiCropSimclrInfoNCECriterion
  from vissl.losses.simclr_info_nce_loss import SimclrInfoNCECriterion
  from vissl.losses.swav_loss import SwAVCriterion
label_desc: Use image node_id 2 for calling the TestCrossEntropyMultipleOutputSingleTargetLoss obj's underlying member method code with example usage: obj.test_multiple_inputs_single_target(batch_size, target_count, input_count) without return types