class_docstr: Decoder for using inner product for prediction.
class_docstr_tok: ["Decoder","for","using","inner","product","for","prediction","."]
code: def __init__(self, dropout, act=torch.sigmoid):
      super(InnerProductDecoder, self).__init__()
      self.dropout = dropout
      self.act = act
  
file_path: graph4nlp/graph4nlp/pytorch/test/link_prediction/model.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from layers import GraphConvolution
  from ...modules.prediction.classification.link_prediction.ConcatFeedForwardNNLayer import ConcatFeedForwardNNLayer
  from ...modules.prediction.classification.link_prediction.ElementSumLayer import ElementSumLayer
  from ...modules.prediction.classification.link_prediction.StackedElementProdLayer import StackedElementProdLayer
label_desc: Use image node_id 1 to create a new InnerProductDecoder object from inherited base classes: nn with example: obj = InnerProductDecoder(dropout, act)