class_docstr: Implementation of the matrix-tree theorem for computing marginals
  of non-projective dependency parsing. This attention layer is used
  in the paper "Learning Structured Text Representations"
  :cite:`DBLP:journals/corr/LiuL17d`.
code: def __init__(self, eps=1e-5):
      self.eps = eps
      super(MatrixTree, self).__init__()
  
imports: import torch.nn
  import torch
  import torch.cuda
label_desc: Use image node_id 1 to create a new MatrixTree object from inherited base classes: nn with example: obj = MatrixTree(eps)