class_docstr: Implementation of SelfAttentionPooling
  Original Paper: Self-Attention Encoding and Pooling for Speaker Recognition
  https://arxiv.org/pdf/2008.01077v1.pdf
  Taken from: https://gist.github.com/pohanchi/c77f6dbfbcbc21c5215acde4f62e4362
code: def __init__(self, input_dim):
      super(SelfAttentionPooling, self).__init__()
      self.W = nn.Linear(input_dim, 1)
  
imports: import math
  import numpy
  import torch
  import torch.nn
  from torch.cuda.amp import custom_bwd, custom_fwd
label_desc: Use image node_id 1 to create a new SelfAttentionPooling object from inherited base classes: nn with example: obj = SelfAttentionPooling(input_dim)