class_docstr: Sigmoid (binary) classifier for sentence-level relation extraction.
docstr: Args:
      args: depends on the encoder
  Return:
      logits, (B, N)
docstr_tok: ["Args",":","args",":","depends","on","the","encoder","Return",":","logits",",","(","B",",","N",")"]
code: def forward(self, *args):
      """
      Args:
          args: depends on the encoder
      Return:
          logits, (B, N)
      """
      rep = self.sentence_encoder(*args)  # (B, H)
      rep = self.drop(rep)
      logits = self.fc(rep)  # (B, N)
      return logits
  
file_path: OpenNRE/opennre/model/sigmoid_nn.py
imports: import torch
  from torch import nn, optim
  from .base_model import SentenceRE
label_desc: Use image node_id 2 for calling the SigmoidNN obj's underlying member method code with example usage: obj.forward() and returns: logits