class_docstr: Vocab parallel cross entropy loss for 2.5D parallelism
  
  Args:
      reduction (bool, optional): whether to average the loss, defaults to True.
code: def __init__(self, reduction=True):
      super().__init__()
      self.reduction_mean = reduction
  
imports: import torch
  import torch.distributed
  from torch.cuda.amp import custom_bwd, custom_fwd
  from torch.nn.functional import cross_entropy
  from torch.nn.modules.loss import _Loss
  from colossalai.legacy.context import ParallelMode
  from colossalai.legacy.core import global_context
  from colossalai.legacy.nn.layer.parallel_2p5d import reduce_by_batch_2p5d, split_batch_2p5d
  from colossalai.legacy.nn.layer.parallel_2p5d._utils import assert_tesseract_initialization
  from colossalai.legacy.registry import LOSSES
  from colossalai.utils import get_current_device
label_desc: Use image node_id 1 to create a new VocabParallelCrossEntropyLoss2p5D object from inherited base classes: _Loss with example: obj = VocabParallelCrossEntropyLoss2p5D(reduction)