class_docstr: Description
  -----------
  The attention function. Correspond to :math:`s` in eq.27 the paper.
  
  Parameters
  ----------
  tau : float
      The lower thresholding parameter. Correspond to :math:`\tau` in the paper.
  T : float
      The upper thresholding parameter. Correspond to :math:`T` in the paper.
  p : float
      Correspond to :math:`\rho` in the paper..
  attn_dropout : float
      the dropout rate of attention value. Default: ``0.0``.
  
  Returns
  -------
  torch.Tensor
      The output feature
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code: def __init__(self, tau, T, p, attn_dropout=0.0):
      super().__init__()
  
      self.tau = tau
      self.T = T
      self.p = p
      self.attn_dropout = attn_dropout
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from ....None import function
label_desc: Use image node_id 1 to create a new Attention object from inherited base classes: nn with example: obj = Attention(tau, T, p, attn_dropout)