code: def __init__(self, n=2, ignore_index=-1, reduction="mean"):
      super(TaylorCrossEntropyLossV1, self).__init__()
      assert n % 2 == 0
      self.taylor_softmax = LogTaylorSoftmaxV1(dim=1, n=n)
      self.reduction = reduction
      self.ignore_index = ignore_index
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
label_desc: Use image node_id 1 to create a new TaylorCrossEntropyLossV1 object from inherited base classes: nn with example: obj = TaylorCrossEntropyLossV1(n, ignore_index, reduction)