class_docstr: A special loss containing a BatchNorm module
class_docstr_tok: ["A","special","loss","containing","a","BatchNorm","module"]
code: def __init__(self, num_classes):
      super().__init__()
      self.bn = nn.BatchNorm1d(num_classes)
      self.fc = nn.Linear(num_classes, num_classes)
      self.xent = CrossEntropyLoss()
  
imports: import copy
  import unittest
  from typing import Any, Dict
  from unittest import mock
  import torch
  import torch.nn
  from classy_vision.generic.util import get_checkpoint_dict
  from classy_vision.losses import ClassyLoss, register_loss
  from classy_vision.tasks import build_task, FineTuningTask
  from classy_vision.trainer import LocalTrainer
  from test.generic.config_utils import get_fast_test_task_config
  from test.generic.utils import compare_model_state
  from torch.nn.modules.loss import CrossEntropyLoss
label_desc: Use image node_id 1 to create a new BatchNormCrossEntropyLoss object from inherited base classes: ClassyLoss with example: obj = BatchNormCrossEntropyLoss(num_classes)