class_docstr: Self attention over a sequence:
  * o_i = softmax(Wx_i) for x_i in X.
code: def __init__(self, input_size):
      super(LinearSeqAttn, self).__init__()
      self.linear = nn.Linear(input_size, 1)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
  import sru
label_desc: Use image node_id 1 to create a new LinearSeqAttn object from inherited base classes: nn with example: obj = LinearSeqAttn(input_size)